Epidemiological studies have, so far, identified factors associated with increased risk for incident or progressive OA, such as age, sex, heredity, obesity, and joint injury. There is, however, a paucity of long-term data that provide information on the nature of disease progression on either group or individual levels. Such information is needed for identification of study cohorts and planning of clinical trials. The aim of the study was, thus, to assess the variation in pain and function on group and individual level over 2 years in previously meniscectomized individuals with and without radiographic knee osteoarthritis (OA).143 individuals (16% women, mean age at first assessment 50 years [range 27–83]) were assessed twice; approximately 14 and 16 years after isolated meniscectomy, with a median interval of 2.3 years (range 2.3–3.0). Radiographic OA  was present in the operated knee in 40%, and an additional 19% had a single osteophyte grade 1 in one or both of the tibiofemoral compartments. Subjects completed the self-administered and disease-specific Knee injury and Osteoarthritis Outcome Score (KOOS).There were no significant changes in the group mean KOOS subscale scores over the 2-year period. However, a great variability over time was seen within individual subjects. Out of 143 subjects, 16% improved and 12% deteriorated in the subscale Pain, and 13% improved and 14% deteriorated in the subscale ADL ≥ 10 points . Similar results were seen for remaining subscales.Group mean scores for this study cohort enriched in incipient and early-stage knee OA were similar over 2 years, but pain, function and quality of life changed considerably in individuals. These results may be valid also for other at risk groups with knee OA, and motivate further careful examination of the natural history of OA, as well as properties of the OA outcome instruments used. Longitudinal outcome data in OA studies need to be analyzed both on an individual and a group level. Drugs that may slow or halt the breakdown of cartilage and other joint tissues in osteoarthritis (OA) and possibly improve symptoms and function are now being developed in the pharmaceutical industry. The potential availability of disease modifying OA drugs has focused attention on our relative lack of information on the 'natural disease history' of OA with regard to changes in symptoms, functional limitations, joint structure and other markers of disease change .Epidemiological studies have identified factors associated with increased risk for incident or progressive OA, such as age, sex, heredity, obesity, and joint injury, pain, alignment, or laxity. There is, however, a paucity of long-term data that document the rate and nature of natural OA disease progression on either group or individual levels. Such information is needed for identification of study cohorts and planning of clinical trials of disease modifying OA drugs. Even more importantly, knowledge of natural disease progression in different patient groups will be needed to select those future groups that may benefit from such drugs.Only a few of the previously published studies have presented information on longitudinal variation in pain and function in the natural history of knee OA. The "Bristol 500 OA study" noted, that although pain changed little on a group level over a 3-year follow-up period, it varied greatly in individuals, with some subjects reporting marked improvements. Similarly, a minority improved functionally -4.Yet another report suggested that most patients with OA attending rheumatology clinics do not deteriorate radiographically or symptomatically over an 11-year period . A more However, outcome is usually heterogeneous: study subjects may report improvement or deterioration while they do not change radiographically over the time period assessed. It may also be that a few individuals alone generate much of any change detected at group level -11. A fuThe objective of this investigation was to assess both group and individual variation in knee pain, function and quality of life over two years in a study group enriched in incipient and early-stage radiographic knee OA.Approval was obtained from the Research Ethics Committee of the Medical Faculty of Lund University, Sweden. All patients who underwent meniscectomy between 1983 and 1985 were identified by searching the surgical records at the Department of Orthopedics, Lund University Hospital. In this period 552 meniscectomies were performed. Inclusion and exclusion criteria  who returned the questionnaires, 6 were excluded because they matched one of the exclusion criteria. At 2 years after the first assessment 5 subjects had died, but the remaining 200 individuals were asked to provide a second evaluation using an identical questionnaire. Replies were received from 143 (72%). Of these 143 participants, 102 were meniscectomized by open surgery, and 41 by arthroscopy. Nineteen underwent an additional meniscus operation in the index knee.All re-operations were performed within 3 years after the original meniscectomy. Twenty-three participants were treated with subsequent meniscectomy of the contralateral knee. One of them underwent high tibial osteotomy and 1, because of OA, received a knee prosthesis in the contralateral knee. Data concerning subsequent surgeries were based on the medical records of Lund University Hospital and on self-reported information.At the time of the participants' second evaluation with questionnaires, standing anteroposterior (AP) radiographs of both knees were taken in 15 degrees of flexion using a CGR Phasix 60 generator at 70 kV, 16 mA, film-focus distance 1.5 m (CGR, Liège, Belgium). Ten out of the 143 participants (7%) declined the radiographic examination. All AP radiographs of the tibiofemoral joints from the follow-up were assessed for joint space narrowing (JSN) and osteophytes according to the atlas from Osteoarthritis Research Society International (OARSI) .The presence of these features was graded on a 4-point scale (range 0–3, with 0 = no evidence of bony changes or JSN). We considered radiographic knee OA to be present if any of the following criteria was achieved in any of the 2 tibiofemoral compartments: JSN ≥ grade 2 or the sum of the 2 marginal osteophyte grades from the same compartment ≥ 2, or JSN grade 1 in combination with an osteophyte grade 1 in the same compartment ,14. ThisThe Knee injury and Osteoarthritis Outcome Score (KOOS, Swedish version LK 1.0) is a 42-item self-administered knee-specific questionnaire based on the WOMAC Osteoarthritis Index ,17. KOOS. The KOOS is valid, reliable and responsive in follow-up of meniscectomy [The questionnaire and scoring manual can be downloaded from scectomy , anterioscectomy  and totascectomy . The parThe minimal perceptible clinical improvement (MPCI) represents the difference on the measurement scale associated with the smallest change in the health status detectable by the individual. Since the KOOS questionnaire contains the full and original version of the WOMAC LK 3.0 index, we used the MPCI as described for WOMAC . Thus, aP-values for categoric data were calculated with Fisher's exact test. All tests were 2-tailed and a P-value of ≤ 0.05 was considered statistically significant (SigmaStat, version 2.0, for Windows).If questions were left unanswered in any part of the questionnaire, we returned the questionnaire to be completed. The questionnaires were then completed fully. The Mann-Whitney U-test was used to determine differences between the groups. The study group comprised 143 individuals, of whom 23 (16%) were women. The participants' mean age at the first follow-up was 51 (range 27–83) years. The assessment was carried out twice: at approximately 14 and 16 years after the surgery, with a median interval of 2.3 (range 2.3 to 3.0) years. Fifty-three (40%) of the 133 individuals who had undergone radiographic examination had radiographic tibiofemoral OA in their index (operated) knee (21% women, age range 29–83, mean 53) and 80 were classified as non having OA (11% women, age range 27–82, mean 50). An additional 25 (19%) (not classified as radiographic OA) had a single osteophyte grade 1 in either one or both tibiofemoral compartments.P = 0.004), other Symptoms Δ = 9 points (P = 0.013), ADL Δ = 10 points (P = 0.003), Sport/Rec Δ = 17 points (P = 0.005), and QOL Δ = 16 points (P = 0.003) assessed in 2000, and in the dimensions Sport/Rec Δ = 14 points (P = 0.020) and QOL Δ = 12 points (P = 0.041) evaluated in 1998.Mean scores for the KOOS subscales at the first assessment did not change significantly over the 2-year study period Table . MoreoveWe analyzed separately those subjects (N = 57) that did not participate in the second assessment. Their mean KOOS scores at the first examination did not differ significantly from the remainder of the study cohort, indicating little or no inclusion bias for the second follow-up (data not shown). The scores in the 5 patients that underwent additional surgery (e.g. osteotomy, knee arthroplasty) did not differ significantly from the rest of the group.In spite of the lack of change on a group level, we found substantial intra-individual variability in the questionnaire subscale scores measured 2 years apart. Out of the total 143 study subjects, 40 had either improved or deteriorated (n = 23 (16%) and n = 17 (12%), respectively) 10 points or more for the KOOS subscale Pain. Of the 23 subjects who had improved in their pain score by these criteria, 14 had also improved in the subscale Symptoms, 17 in ADL, 16 in Sports/Rec, and 17 in QOL.P = 0.24, Table Only 1 of these subjects deteriorated in Symptoms, and 2 in Sports/Rec, none in the other subscales. Of the 17 subjects who deteriorated in Pain, 13 similarly deteriorated in Symptoms, 12 in ADL, 10 in Sports/Rec, and 10 in QOL. When evaluating those who had undergone radiographic examination, there were no significant differences in variability detected whether the subject had radiographic tibiofemoral OA or not  obtained for the WOMAC; since KOOS contains the WOMAC items and is similar in format. The KOOS subscale ADL is equivalent to the WOMAC subscale Function, while new items have been added to the KOOS subscales Pain and Symptoms. The dimensions assessed by the KOOS subscales Sport and Recreation Function and knee-related Quality of Life are not assessed by the WOMAC. The MPCI for the WOMAC is in the range of 8 to 12 points on a 0–100 scale .This threshold coincides with the change observed in KOOS scores between 3 and 6 months postoperatively when assessing rehabilitation following reconstruction of the anterior cruciate ligament and concurs with the OARSI definition of moderate improvement in the knee pain assessment for clinical trials in OA ,22. HoweIt may be argued that the subject-related changes observed in this study represent inherent instrument instability. However, validation studies of KOOS support the reproducibility and stability of the KOOS instrument -19. TestThe proportion of subjects changing over 5 days was approximately half of that changing over 2 years in the present study, in further support that the variation in the present study cannot be explained solely by instrument noise (data not shown). A 'frame shift' in the priorities of the individual patient may occur during long term studies. However, we suggest that a significant frame shift is unlikely to have occurred over this 2 year study period of a cohort with a mean age of 50 years.Significant change of KOOS scores over time were noted in 1/3 of the cohort studied. About half of those who changed clinically improved. This was true in particular for patients with lower (worse) baseline scores. It is thus possible that the lower proportion of 'changers' among those with better baseline scores may have been, at least in part, due to a ceiling effect.We conclude that despite unchanged group mean scores over 2 years, pain, function and quality of life change considerably over time in individuals, in this study cohort enriched in incipient and early-stage knee OA. These findings may be applicable also to other at risk patient groups in different phases of OA development, and motivate further careful examination of the natural history of OA, as well as properties of the OA outcome instrument used. We suggest that longitudinal OA study data should be analyzed both on the individual and group level.Our findings may have further relevance to clinical trials of OA that seek to document long term benefit in the form of symptom improvement and structural improvement. It is clear that much additional effort will need to be spent on selection of groups at high risk of progression of symptoms and structural joint change, and the identification of predictors for deterioration. Our results also suggest that the use of responder criteria may be an important aspect of analyzing the outcome of such trials ,33.EMR and LSL planned study and collected the data. PTP performed the statistical analysis and drafted the manuscript. ME formed the database of patients and participated in the statistical analysis. ME, EMR, LSL corrected the manuscript. All authors read and approved the manuscript


Obesity is a growing international health problem that has already reached epidemic proportions, particularly within the United States where a majority of the population is overweight or obese. Effective methods of treatment are needed, and should be taught to physicians by efficient means. There exists a disconnect between the rising obesity prevalence with its high toll on medical resources, and the lack of obesity education provided to practitioners in the course of their training. One particular shortfall is the lack of representation of obesity on standardized medical examinations. Physician attitudes toward obesity are influenced by their lack of familiarity with the management of the disease. This may include dietary restriction, increasing physical activity, behavior modification, pharmacotherapy, and surgical interventions. Thus, curricular changes in the medical education of obesity could help reduce morbidity and mortality associated with this disease. Wegeners's granulomatosis, errlichiosis, and tetrology of Fallot are examples of some of the rare diseases that I have learned to identify and look for in patients for over seven years as a medical student and resident in Internal Medicine. As a physician in training, I was frequently challenged to consider broad differentials and to watch out for the zebra that masquerades as a common disease throughout my clinical encounters. I have had my antennas up in search of these diseases for quite a while now. I have not, however, encountered any patients with these diseases so far. What I have usually encountered instead are common diseases, like type 2 diabetes, hypertension, and arthritis. More than anything, I have been struck by the incidence of obesity in our population. I find it alarming that many clinicians fail to actively address this growing epidemic in a formal manner with their patients, but rather regard obesity as a lifestyle choice that is the patient's sole responsibility.My personal experience with obesity, having trained at a quaternary referral center in the relatively thin state of California, is that over one third of the patients I cared for were obese (not just overweight). Consistent with national trends, patients in my region have been becoming more obese and accordingly have been suffering increasingly from the complications of the disease, such as hypertension, insulin resistance, fatty liver disease, dyslipidemia, coronary heart disease, osteoarthritis, obesity-related cancer, and premature death . I have Many physicians cite their unfamiliarity with obesity as an impediment to their ability to adequately address the problem with their patients . In one I recalled at least five examination questions addressing Wegener's granulomatosis, but none directly on obesity. The differences in prevalence are remarkable. In the United States, approximately 61% (110 million) of adults (age 20–74 years) are overweight or obese. . EducatoDiabetes, coronary heart disease, dyslipidemias, hypertension, and cancer were appropriately well represented in this ABIM exam and previous standardized examinations I have taken. Obesity should be right up there with these "big players". There is a lot to understand within this field. It is a lot more complex than "eat less, make better nutritional choices, and exercise more". The complexities of nutritional decision making are very important to the patient, and they want to discuss these choices with physicians as well as dieticians. Pharmacotherapy, although limited in terms of number of options, does have a role. Bariatric surgery is an evolving field and there are complexities associated with the use of the procedure that surgeons and internists alike must understand. Also, such psychosocial aspects of obesity as diminished quality-of-life, self-esteem, and work performance must be stressed and understood. Fogelman reported that in one survey of family practitioners, 72% believed that they had limited efficacy in treating obesity and considered themselves not well prepared by medical school to treat overweight patients . Some 60Primary prevention is the way to go in obesity research expenditure. In my opinion, the greatest healthcare cost-savings' "bang-for-the-buck" comes from preventive care and education. Consider how many fewer cases of diabetes, hypertension, CHD, fatty liver disease, dyslipidemia, thromboembolic disease, obesity-hypoventilation, obstructive sleep apnea, gout, osteoarthritis, cancer, GERD, reproductive and urinary tract abnormalities, cataracts, psychosocial abnormalities we would have to battle if the inciting factor (obesity) was aggressively treated at the onset. Is this not one prudent management step toward curtailing an overtaxed health care system?The war on obesity seems winnable. We just need the tools and awareness to address the disease. Obesity is not a silent disease to be tolerated: it is an aggressive yet insidious disease (much like type 2 diabetes) that must be arrested before its negative health consequences become irreversible. The first step is to teach practitioners what to look out for, and in turn, to teach patients what to look out for. Meanwhile, I will have my antennas up in search of Wegener's granulomatosis.I hereby declare that I do not have a financial association or other conflict of interest with the subjects mentioned in this manuscript.


Why are the prevalence and severity of asthma increasing? Platts-Mills looks at the key studies that can help to anwer this important question Over the last hundred years, there have been major triumphs in medicine related to public health, vaccination, and the introduction of new medicines. However, over the same period, several diseases have increased in prevalence and/or severity. In some cases, the causes of the increase have become obvious—the increases in lung cancer, coronary artery disease and type 2 diabetes, for example, are not considered to be a mystery. On the other hand, a large group of diseases related broadly to “inflammation” have also increased. For these, a wide range of hypotheses about causation have been proposed. Type 1 diabetes, rheumatoid arthritis, and inflammatory bowel disease have increased since 1980 [The major changes in rural areas, tropical villages or in Europe pre-1900 that could be related to the change in immune responses include: decreases in helminth infection; physical proximity to farm animals ; exposurHay fever became a problem in Northern Germany and England as early as 1900. Clear evidence for this view comes from Noon's description of the development of immunotherapy for hay fever in 1911, the studies on hay fever prevalence by Ratner and Silverman in New York in 1935, and the recognition that hay fever was a major community problem in New York in 1946. More recently, Harold Nelson analyzed all the studies on hay fever published in the United States and found a prevalence of ~15% in 1960, with no convincing evidence of an increase since then .If seasonal hay fever was epidemic in 1960, then the subsequent increase in asthma has to be seen in a different light. The best estimates for the start of the asthma epidemic are around 1960 for such diverse populations as army recruits in Finland , school Several hypotheses have been proposed to explain the increase in asthma . At thisHypothesis 1: Increased exposure to perennial allergens, e.g., dust mitesFor:(A) Housing changes: houses are built more tightly and are more well insulated; more furnishings; fitted carpets, and (B) more time spent indoors. Increased exposure leads to increased sensitization.Against: Increases in asthma have been seen in countries where dust mites are not present in homes, and in the Netherlands the concentration of mite allergens has actually decreased by as much as tenfold over the past 15 yearsHypothesis 2: Changed immune responsiveness is due to cleanliness For:(A) Bacterial and other infections have decreased due to improved hygiene, immunization, and antibiotics, and (B) changed gut flora (antibiotics, diet, etc.). Change from Th1 to Th2 leads to increased allergy.Against: In New York City, the increase in seasonal hay fever occurred 30 years before the increase in asthma, and in Africa, children whose families move into cities, including informal settlements, have experienced increases in infections, wheezing, and diagnosed asthmaHypothesis 3: Loss of a lung-specific protective effect, 1960–2000For:(A) Changing diet leads to a changed inflammatory response, and (B) decline in physical exercise. Increased wheezing among allergic children.Against: This is unlikely to be just be a lung-specific effectDermatophagoides pteronyssinus (dust mites), the strong association between this allergen and asthma was established in many parts of the world, with odds ratios as high as 6 or even 10 [Long before the first case control or prospective study, the association between allergy and asthma was obvious in case series. These earlier studies reported skin testing with an amorphous extract called “house dust,” but it was not until the identification of dust mites that the association was clarified . Indeed, even 10 ,8. The p even 10 . The coh even 10 . These s even 10 . This isSince assays for total serum IgE became available in the 1970s, it has been clear that patients with asthma have, on average, higher total IgE than patients with hay fever or no allergy. Indeed, by 1980 this was considered an established fact in textbooks of immunology. It was assumed that the increased total IgE related to allergen-specific responses. However, in some studies, the association between total IgE and asthma was stronger than the association between asthma and specific IgE. In 1989, Burrows et al. went further and suggested that specific IgE correlated with hay fever, while total IgE correlated with asthma . The impThe strength of the association between asthma and total IgE raises questions that have not been resolved. Do specific IgE antibody responses contribute to or even push total IgE? If so, do the IgE antibody responses to some allergens have more effect than others? This question is relevant both to attempts to explain major differences in total IgE between countries and to studies on acute asthma. In emergency room and hospital studies, the geometric mean total serum IgE of patients with asthma is often greater than 200 IU/ml higher than values found in population-based studies. Recent work from Heymann et al. and Green et al. on patients hospitalized for asthma has suggested that the interaction between rhinovirus and allergy occurs predominantly among patients with total IgE > 200 IU/ml . Thus, tAntigen exposure is considered to be a primary requisite for immune responses, and allergen-specific responses are no exception. There are many examples of allergens that are not significant in areas where the allergen is not encountered. For example, the pollen of olive trees is not relevant in northern countries, dust mite allergens are not significant in the northern part of Scandinavia or the mountain states of the United States, and cockroach allergens are not significant in suburban areas of the United States, the United Kingdom, or New Zealand.For dust mites, there is a wide range of evidence that increased exposure increases sensitization. Homes in Sweden, Berlin, the United Kingdom, and New Zealand have progressively higher concentrations of mite allergen and progressively higher prevalence of sensitization to mite allergens . But theIn fact, children raised in a house with a cat were less likely to be sensitized to cats . InitialOne of the central assumptions of the cleanliness hypothesis is that regulation of immune responses is, at least in part, non-specific. It is assumed that helminth infection, mycobacteria, Hepatitis A, endotoxin, and early-life infections can create a milieu that leads to a decrease in allergic responses in general. Likewise, we might expect that exposure to high concentrations of cat allergen, which can induce IL-10 producing cells, should have a general effect. There is some evidence for this hypothesis. In Detroit, the presence of two or more animals in the house tended to reduce allergy in general. In Sweden, the presence of a cat in the house is associated with decreased sensitization to cat, and also to birch and dog. However, in the United States and New Zealand, the presence of a cat in the home has no effect on the prevalence or titre of IgE antibody to dust mites ,17. ThusOver the last half of the 20th century, there have been major changes in diet and physical activity. The most obvious result of these changes is an increase in obesity, which has reached epidemic proportions in the United States. Since 1994, there have been multiple reports of an association between elevated body mass index (BMI) and asthma . Thus, tIt is much easier to document BMI than diet or physical activity, and although some of the obesity data are convincing, they are not consistent and certainly not comparable to the association between obesity and diseases such as type 2 diabetes in childhood. In a typical study, Camargo et al. found that the prevalence of wheezing was 13% among the heaviest quintile and 7% among the lowest quintile for BMI . ComparaStudies using questionnaires have attempted to ask whether there is a relationship between wheezing and physical activity. However, the track record for questionnaires on this subject is very poor. Westerterp and his colleagues have reported two observations: first, that general activity contributes more to energy consumption than “aerobic exercise” does and second, that many subjects who initiate an exercise program (such as a twice weekly visit to the gym) overcompensate so that they actually decrease overall activity . RecentlThe next question to ask is whether physical activity would have a beneficial effect on asthma? Fredburg concluded that full expansion of the lungs had a more potent effect on bronchial smooth muscle than isoprenaline . Togias A different explanation for the effects of physical activity comes from evidence that physical activity can be “anti-inflammatory.” This evidence relates to several different models though not at present to the lungs. In some studies, obesity appears to be a risk factor for wheezing among non-allergic children. However, in most studies, the association between allergen sensitization and asthma has been found in obese and non-obese children equally . ObviousAlthough the explanation for the increase in asthma is not yet clear, it is possible to put forward a model that includes elements of each of the three main hypotheses. Children raised in the tropics, on farms, or in villages such as those in Africa or Papua New Guinea have exposure to endotoxin or infections sufficient to interfere with the development of allergen-specific IgE antibody responses. Once water supplies are clean, and major infectious diseases have been controlled, allergic diseases will appear.However, asthma appears to be associated with perennial, i.e., indoor exposure, and may be more common or more severe in countries where mites or cockroaches are the major source of allergens. Even with indoor allergen exposure, wheezing may remain transient or mild, provided prolonged outdoor play is normal. It is the combination of the control of infectious diseases, prolonged indoor exposure, and a sedentary lifestyle that is the key to the asthma epidemic and, in particular, the key to the rise in severity. Using this analysis, the severity of asthma in North American cities becomes much easier to explain. Children in New York, Atlanta, Philadelphia, and Washington, D.C. spend long hours indoors, have high exposure to mite, cockroach, and/or rodent allergens, and have very low levels of physical activity.In conclusion, it appears that these combined factors are the key to the asthma epidemic and, in particular, the key to the rise in severity. We clearly need to develop ways to increase prolonged physical activity, both among patients with asthma and in the general population. We also need to investigate whether prolonged moderate activity is beneficial in the treatment of asthma and/or is “anti-inflammatory.” What is equally clear is that the current obsession of the medical profession with the pharmaceutical management of asthma (as well as other lifestyle-related diseases) does not address the reasons why the disease has become so common and so severe.


PTEN and CDKN2A alterations are key genetic events in tumor initiating cells with neural precursor properties.Pediatric brain tumors may originate from cells endowed with neural stem/precursor cell properties, growing in vitro as neurospheres. We have found that these cells can also be present in adult brain tumors and form highly infiltrating gliomas in the brain of immunodeficient mice. Neurospheres were grown from three adult brain tumors and two pediatric gliomas. Differentiation of the neurospheres from one adult glioblastoma decreased nestin expression and increased that of glial and neuronal markers. Loss of heterozygosity of 10q and 9p was present in the original glioblastoma, in the neurospheres and in tumors grown into mice, suggesting that  Recent data have proposed that brain tumors contain a "core" of stem cells providing them with the potential to grow aggressively, escaping the effects of radiotherapy and chemotherapy ,2. TheseSuch observations, derived from pediatric tumors only, did not include data on the in vivo tumorigenicity of cancer stem cells. We have found that neurospheres from an adult glioblastoma (GBM) have the potential to express glial and/or neuronal markers and form highly infiltrating gliomas into the brain of immune-deficient mice.The neurospheres were derived from three adult brain tumors and two pediatric malignant gliomas  neurospheres into nude mice. All the mice injected intracerebrally (i.c.) with BT1 neurospheres, but none of those injected subcutaneously (s.c.), developed brain tumors that were lethal after 3, 5 and 6 months, respectively. After 4 months, however, none of the mice injected with BT2 neurospheres developed a tumor. Adherent cells from the same two patients were also injected i.c. and s.c. into nude mice. Two of three mice injected i.c. with BT1 adherent cells, but none of those injected with BT2 cells, developed a brain tumor that were lethal 4 and 5 months after injection, respectively.All the brain tumors in nude mice appeared as large, infiltrating gliomas Fig.  with feaThe five chromosomal regions showing frequent allelic imbalance in gliomas (1p, 9p, 10q, 17p and 19q) were investigated on six specimens obtained from BT1 surgery. No allelic loss was detected in specimen 1 ; S2 and S3  showed LOH on chromosome 10q; S4 and S5  had LOH on 10q and 9p . p16 expression is absent or defective in glioblastomas [Second, the tumors obtained from neurospheres were completely different from those obtained from established cell lines like U87, 9L, C6 or F98: they grew slower, were highly infiltrating and showed a morphological pattern resembling that of an anaplastic, mixed glioma, but without necrotic areas and palisade cells typical of a GBM  contains Methods with references, comments on in vitro data and the legend to the additional file 2.Click here for fileAdditional file 2  contains figures of brain tumor neurospheres, and flow cytometry and immunohistochemical data for their characterization.Click here for file


Arabidopsis in vitro transcripts and arrayed serial dilutions of homologous probes; 2) how curing time of in-house poly-L-lysine coated slides impacts probe retention capacity; and 3) the retention characteristics of 13 commercially available surfaces.Global gene expression studies with microarrays can offer biological insights never before possible. However, the technology possesses many sources of technical variability that are an obstacle to obtaining high quality data sets. Since spotted microarrays offer design/content flexibility and potential cost savings over commercial systems, we have developed prehybridization quality control strategies for spotted cDNA and oligonucleotide arrays. These approaches utilize a third fluorescent dye (fluorescein) to monitor key fabrication variables, such as print/spot morphology, DNA retention, and background arising from probe redistributed during blocking. Here, our labeled cDNA array platform is used to study, 1) compression of array data using known input ratios of When array element fluorescein intensity drops below 5,000 RFU/pixel, gene expression measurements become increasingly compressed, thereby validating this value as a prehybridization quality control threshold. We observe that the DNA retention capacity of in-house poly-L-lysine slides decreases rapidly over time  and that there are considerable differences in retention characteristics among commercially available poly-L-lysine and amino silane-coated slides.High DNA retention rates are necessary for accurate gene expression measurements. Therefore, an understanding of the characteristics and optimization of protocols to an array surface are prerequisites to fabrication of high quality arrays. The generation of reliable gene expression data with cDNA microarrays requires fabrication of quality arrays. This task encompasses the amplification of adequate amounts of concentrated PCR product for use as probe from the cDNA clone, followed by ordered arraying of the probes onto coated glass slides. The glass slide is a key variable in either spotted cDNA or oligonucleotide array fabrication since it must possess: 1) a uniform surface that yields spots of consistent shape and size, 2) low background fluorescence, and 3) high DNA retention capacity. Since the array is clearly a source of experimental variability, we have developed a novel three-color array approach where it is possible to directly visualize either cDNA or oligonucleotide arrays prior to hybridization [in vitro transcript we experimentally correlate the quantity of support bound probe to measured expression ratios, in order to validate our quality control threshold for array acceptance. We then utilize our three-color array platform to evaluate the characteristics of in-house prepared poly-L-lysine coated slides and 13 additional commercially available coating surfaces, in terms of background auto-fluorescence, spot morphology, and DNA retention.By labeling the array itself with a third color, we have observed that arrays fabricated together are not equivalent in terms of a number of measurable physical parameters, including the amount of DNA probe deposited and retained and the amount of background arising from probe solublized and re-deposited during post-processing. In prior studies, we observed that these pre-hybridization array-based variables play a direct and significant relationship in replicate consistency, and that microarray data quality can be improved through prehybridization slide selection based upon these quality parameters ,2. As a Saccharomyces cerevisiae probes and complementary Cy5 and Cy3 labeled cDNA targets derived from in vitro transcripts, indirectly demonstrated this by printing yeast probes at increasingly dilute concentrations (<50 ng/ul) and observed elimination of the measured dynamic range to where input transcript ratios of 30:1 or 1:30 were both detected as output ratios close to 1:1, illustrating that limiting bound probe results in an underestimation or failure to detect differential gene expression [It has been assumed that the amount of cDNA probe deposited and retained on the array surface would have a nominal effect on observed differential expression ratios due to the competitive nature of two channel fluorescent hybridizations ; howeverArabidopsis probes and transcripts. Total thymus RNA extracted from the DR+/+ and DRlyp/lyp [Arabidopsis gene in vitro transcript and hybridized to 18,000 probe rat cDNA arrays possessing serially diluted fluorescein-labeled Arabidopsis probes (cellulose synthase, chlorophyll a/b binding protein, and ribulose-1,5-bisphosphate and triosphosphate isomerase, 1:2 dilution series printed at 200 ng/ul to 6.25 ng/ul). This approach allowed comparison of known RNA input ratio to measured output ratio, enabling a direct and quantitative measure of the relationship between the amount of support-bound probe and ratio data compression  were filtered; these spots were either saturated or possessed high background. Spots with low hybridization intensities, which would normally be flagged by Matarray, were intentionally retained to study ratio compression due to low amounts of support-bound probe. After filtering, 896/1536 data points from 16 different arrays were available for analysis. Plotted on the y-axis of Figure Arabidopsis in vitro transcript output log ratio divided by the log ratio of transcript actually introduced into the Cy3 and Cy5 labeling reactions. In this analysis, a perfect measurement is represented by a value of "1". On the x-axis, is plotted the spot fluorescein intensity. When the spot fluorescein intensity falls below 5000 RFU/pixel, the data variability and data compression  dramatically increase. These results recapitulate our previous observations where replicate consistency was found to decrease when the array average spot fluorescein intensity dropped below 5000 RFU/pixel, whereas arrays possessing average fluorescein intensities above 5000 RFU/pixel were found to generate equally good data. These results further demonstrate that use of measurable array characteristics are effective quality markers for printed arrays (judged by their effect on the hybridization data) and serve to validate our array intensity quality control threshold of >5000 RFU/pixel.To expand upon these observations and place them in context with the quality control standards of our three-color array platform, we conducted similar experiments using Rlyp/lyp  BioBreedn Figure  and 1B. ; ; ). Although most available protocols are quite similar, some recommend the curing of slides for two weeks prior to spotting, while others state that coated slides are not stable for extended periods of time and recommend not printing onto slides that are greater than 4 months old. To investigate slide coating age as a potential variable in retention capacity, we fabricated more than 1,000 rat cDNA arrays (18,000 element/slide) using in-house poly-L-lysine coated slides ranging in age from 3 to 12 weeks. These slides were coated in 26 independent sessions and utilized over 12 different print runs. After printing all arrays were post-processed [Clearly, the amount of immobilized probe on the coated glass surface is a critical array fabrication variable, therefore factors that affect the amount of retention characteristics, such as surface chemistry, probe concentration, spotting buffer, spotting conditions, cross-linking and blocking conditions are important to understand. Protocols for coating glass microscope slides with poly-L-lysine are readily available on-line and reasonably simple to perform . An average array fluorescein intensity of >15,000 RFU/pixel was observed when printing on slides 4 weeks old or less, however a nearly 50% reduction in retention capacity is observed when printing on poly-L-lysine coating greater than 10 weeks old. We speculate that the poly-L-lysine may become oxidized thereby losing its positive charge and ability to initially electrostatically interact with the negatively charged DNA. Irregardless of the type of degradation occurring to the surface coating over time, these results indicate that, at least for in house fabricated poly-L-lysine coated slides, shelf-life is a significant variable in the fabrication of quality arrays capable of yielding reliable gene expression measurements.A significant loss of DNA retention capacity is observed Figure  when theGiven the potential time-dependent variability of in-house prepared poly-L-lysine coated slides, we investigated the retention characteristics of commercially available coated slides. Our objective was to identify a surface with consistently higher retention characteristics than our "fresh" in-house slides without having to change the spotting buffer (1.5 M betaine/5% DMSO) or the nonaqueous post-processing protocol ,9, sinceTo study retention characteristics, a single 9600 element human cDNA array was spotted onto each slide in 1.5 M betaine/3%DMSO. The in-house poly-L-lysine slides were less than 6 weeks old and all vendor-supplied slides were unpacked from any special packaging immediately before printing. Five replicate arrays for each slide type were generated. The five replicates were evenly distributed over the arrayer deck (capacity 100 slides) by arranging the slides into 5 groups of 18 to account for any variance introduced through print rank order (ie first versus last), since we previously identified this as a variable that influences array average array fluorescein intensity . The aveIt has been reported that the amount of UV irradiation may be an important array fabrication variable since the amount of hybridization signal from spotted 70-mer oligonucleotides has been found to be dependent on the amount of cross-linking . In thisFabrication of high quality spotted arrays is a daunting task possessing a high number of variables. The vendor supplied slides tested here were done so under conditions that have been optimized for our in-house prepared poly-L-lysine coated slides, although our optimized protocol is not drastically different than those used by other laboratories nor drastically different from any of the vendor provided protocols. Our observations, as well as the observations of others, suggest that optimization of ones protocol to a surface chemistry is an essential first step to generating reliable global gene expression measurements using in-house spotted microarrays.2, 50 mM KCl, 0.2 mM each dNTP (Amersham, Piscataway, NJ), 1 M betaine [Taq polymerase (Roche, Indianapolis IN). Reactions were amplified with a touchdown thermal profile consisting of 94°C for 5 min; 20 cycles of 94°C for 1 min, 60°C for 1 min (minus 0.5° per cycle), 72°C for 1 min; and 15 cycles of 94°C for 5 min; 20 cycles 94°C for 1 min, 55°C for 1 min, 72°C for 1 min; terminated with a 7 min hold at 72° [A sequence-verified human library (Research Genetics, Huntsville, AL), consisting of 41,472 clones or a 36,000 clone rat cDNA library obtained from the University of Iowa was used as a source of probe DNA. Cultures were grown in 150 ul Terrific Broth (Sigma, St. Louis, MO) supplemented with 100 mg/ml ampicillin in 384 deep-well plates (Matrix Technologies, Hudson, NH) sealed with air pore tape sheets  and incubated with agitation for 14–16 hr. Clone inserts were amplified in duplicate in 384-well format from 0.5 ul bacterial culture or from 0.5 ul purified plasmid (controls only) using 0.26 μM of each vector primer  as part of the SpotReport®-10 Array Validation System. Arabidopsis thaliana PCR product was cloned into the pCRII vector using the TA cloning kit (Invitrogen, Carlsbad CA) and fluorescein-labeled PCR products for photosystem I chlorophyll a/b-binding protein, RUBISCO activase, ribulose-1,5-biphosphate carboxylase/oxygenase, lipid transfer protein 6 lipid transfer protein 5, papain-type cysteine endopeptidase, root cap 1, and triosphophate isomerase were generated using vector-specific primers essentially as described above. Products were purified, quantified, and a 1:2 dilution series (200 ng/ul to 12.5 ng/ul) was prepared and printed in duplicate onto each array.2, deceleration: 100 cm/sec2. All slides were post-processed using the previously described non-aqueous protocol [2 UV cross-linking energy. This protocol has yielded more favorable fluorescein post-blocking signal-to-noise values  as compared to blocking in aqueous solutions[Poly-L-lysine coated slides were prepared in-house as previously described  on Corniprotocol  using 60solutions,8,17.. Known input ratios of photosystem I chlorophyll a/b-binding protein (30:1); RUBISCO activase (10:1); ribulose-1,5-biphosphate carboxylase/oxygenase (5:1); lipid transfer protein 6 (1:1); 0.7 lipid transfer protein 5 (1:1); papain-type cysteine endopeptidase (1:5); root cap 1 (1:10); and triosphophate isomerase (1:30) were spiked into Cy3 and Cy5 RNA labeling reactions, respectively. After hybridization, arrays were scanned with a ScanArray 5000 (GSI Lumonics, Billerica, MA) and image files were obtained. Again, array image files were analyzed with the Matarray software [Isolation of mRNA, labeling, and hybridization were performed as described previously software ,17.MJH and XW conceived of the study, its design and coordination, and drafted the manuscript. LM, JT, and SM carried out the array fabrication and gene expression studies. XW performed the statistical analysis. All authors read and approved the final manuscript.


The use of spatially referenced data in cancer studies is gaining in prominence, fueled by the development and availability of spatial analytic tools and the broadening recognition of the linkages between geography and health. We provide an overview of some of the unique characteristics of spatial data, followed by an account of the major types and sources of data used in the spatial analysis of cancer, including data from cancer registries, population data, health surveys, environmental data, and remote sensing data. We cite numerous examples of recent studies that have used these data, with a focus on etiological research. Understanding the spatial patterns of diseases in a population can provide insight as to their causes and controls. Indeed, this notion is at the very root of the field of epidemiology . The recThe purpose of this article is to provide an overview of spatial data and its relevance to population-based cancer surveillance and research in the United States as of 2004. We begin by discussing a number of the distinctive characteristics of spatial data, which can sometimes hinder efforts to understand cancer etiology. We then proceed to describe the kinds of data sets that are available, accompanied by a survey of some applications using these data. Finally, we discuss several ongoing efforts to provide central repositories of geospatial data. Given the vast scope of cancer research taking place worldwide, our survey is necessarily partial, and we have chosen to emphasize etiology over other research themes with spatial dimensions, such as patterns of treatment or access to care [Spatial data refer to data with locational attributes. Most commonly, locations are given in Cartesian coordinates referenced to the earth's surface. These coordinates may describe points, lines, areas or volumes. This need not be the only spatial framework; "relative spaces" may be defined in which distance is defined in terms of some other attribute, such as sociodemographic similarly or connectedness along transportation networks ,4. SpatiIndividual humans represent the basic unit of spatial analysis in cancer research. Individuals are categorized as either having or not having a disease or attribute of a disease, and are assigned coordinates corresponding to the location of their place of residence, a technique known as geocoding. As with all measurements, geocoding involves some error. A growing body of literature is exploring the nature of this error and its potential to bias epidemiologic studies . Among tAssigning individuals to their place of residence also poses problems, although this is usually the only locational information that is available. Often the goal of a geographic analysis is to identify a common environmental exposure in a population, but exposures that are occupational or recreational may not necessarily reveal themselves in a residential analysis. Also, given the long latency period for many cancers and the mobility of the American population, the relevant exposure may be associated with a prior address. Difficult-to-measure behavioral risk factors such as smoking and diet often further confound attempts at geographic analysis.Owing to confidentiality restrictions, researchers outside of central cancer registries typically do not have access to address-level data. In such instances, case data are aggregated by some functional or political unit such as census tract, county or ZIP code. Even when the case data are geocoded, population data must be aggregated, at least to the level of the census block, which is the smallest unit for which any population information is available. Knowing that there are four women with breast cancer living on the same street is not sufficient, by itself, to draw conclusions about whether the street displays an unusual incidence pattern; one must also know the number and ages of women without breast cancer on the same street. Short of conducting one's own thorough door-to-door census, this question cannot be answered, except by aggregating the street segments into blocks. When additional variables, such as measures of income or education, or also of interest, then still larger analytical units must be chosen.The necessity for aggregating spatial data raises a whole set of analytic issues regarding the extent to which the act of aggregating introduces error and bias. It is theoretically possible to achieve dramatically different, even contradictory results, simply as a consequence of aggregating the data in a different fashion . This isIn practice, well-chosen scales and groupings can minimize the modifiable areal unit problem and allow reasonable consistency between aggregated and individual-level results . There wOften analyses need to be performed on data that was collected at different spatial scales, such as a study using cancer cases aggregated by ZIP code and modeled air pollutant data at the census tract level. The resulting scale-translation problem is a recurring one that has inspired many independent solutions, and is known variously as areal interpolation, the polygon overlay problem, and the problem of inference with spatially misaligned data, among other terms . The mosSpatial autocorrelation is another distinctive quality of spatial data that requires the use of specialized analytic methods. Spatial autocorrelation is the tendency for nearby observations to have correlated attribute values. For most data sets involving the distribution of human populations and their characteristics, spatial autocorrelation is positive, meaning that neighboring individuals tend to have similar characteristics. Understanding the characteristics and qualities of spatial autocorrelation is essential to adequately model and interpret geographic patterns. For example, it is not appropriate to perform ordinary least squares regression on spatial data, because the presence of spatial autocorrelation means that the observations are not independent. Performing such a regression generally results in downwardly biased estimations of variance, which yields overstated levels of significance. In general, spatially autocorrelated data is less informative in a model than uncorrelated data. There is an ample literature on assessing and properly accounting for spatial autocorrelation in geographic analysis ,27.A final critically important characteristic of spatial data is spatial nonstationarity, or the tendency for relationships between and among variables to vary by geographic location . First-oLocal statistics are less adept at accounting for second-order nonstationarity. Indeed, many of these methods require the assumption of constant variance across space. Because of the uneven distribution of human populations, this assumption is seldom met for health data. Specifically, disease rates in areas with smaller numbers of cases are more variable than those in areas with larger numbers of cases, a property that has also been termed "variance instability" . VariancEfforts to include information about data uncertainty have shown promise, but have not seen widespread use . One comIn this section we described the primary types and sources of data most frequently used in the geographic analysis of cancer, along with examples of their application. These are summarized in Table A cancer registry is a data collection system that tracks cancer cases that have been diagnosed or treated in a specific institution or geographic area. Cancer registries typically collect information from medical records provided by hospitals, doctors, other care facilities, medical laboratories, and/or insurers. Data collected by cancer registries is stored under secure conditions so as to protect confidentiality.Historically, observed geographic differences in cancer incidence have been of great interest in trying to understand more about factors which may influence risk of these diseases. Such differences have served as the basis for studies of migrant populations and acculturation differences in migrant groups. They have been possible because cancer is one of the few chronic diseases for which high quality population-based disease surveillance systems have been in place for many years in many countries of the world.Cancer registry data has been widely applied toward the production of cancer atlases , studiesFor these types of studies, cancer registry data offer both a number of strengths and limitations. Primary strengths include the comprehensiveness of geographic coverage, detailed information on disease subgroups, and rich covariable information on demographic characteristics for each newly diagnosed case of cancer. Because registry data are abstracted from medical records and reflect information for a snapshot in time, primary limitations include the lack of historical information on various factors of potential interest including residential mobility and relevant personal behaviors. Cancer registries typically collect information on the residential address for individuals newly diagnosed with cancer at the time of that diagnosis. Since this is the locational information which serves as the basis for national and international statistics on area cancer rates, it is also useful for looking at area characteristics associated with rate differences, although inferences about etiologic associations are limited for these long latency diseases, and even more so for residentially mobile populations.The Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute (NCI) offers county-level incidence data for its member registries, which cover part or all of eight states, through its SEER*Stat software. Because it provides direct access to individual cancer records, users must first sign a data access agreement. County-level mortality data for the entire United States, collected and maintained by the National Center for Health Statistics (NCHS), is also accessible through SEER*Stat. These data include all causes of death, not just cancer deaths. Selected county-level cancer data may also be accessed through the NCI's Cancer Mortality Maps and Graphs and State Cancer Profiles web sites. The latter was launched in 2003 and contains a host of innovative statistical graphics. Many individual state registries also offer additional geographically referenced data. For example, the Florida Cancer Data System web site allows users to generate a variety of county- and facility-level tables and county-level maps on demand. The Kentucky Cancer Registry also offers a county-level mapping application. New York State offers a limited set of ZIP code level data for the four most common cancer types in the mid-1990s. Currently, county-level cancer incidence data is not available nationally.. Data are available in three basic formats. American FactFinder is a web-based application that allows users to drill down through geographic levels to find data tables of interest. It is most useful for data queries that are well-focused. Data may also be downloaded through an ftp server. This method obtains raw text files that require computer code to be written before the data can be easily accessed or manipulated. This method is most useful for users with large data needs who are in possession of some database programming skills. The third approach is to purchase DVDs from the Census Bureau's Customer Service center. The DVDs allow data output in many spreadsheet and database formats, facilitating the ability for users to process and analyze the data. There are also a large number of third-party vendors who offer similar services [The United States Census Bureau is the principal source of data on the entire population; most countries have comparable agencies. Since cancer rates are calculated by dividing the number of cases by the number of people at risk, census data is frequently referred to as "denominator data". Census data are readily available in electronic format through the Census Bureau web site, services .The four primary data files emanating from the 2000 census are named Summary File 1 through Summary File 4 (SF1–SF4). SF1 contains population counts by age, sex, race and ethnicity and basic housing characteristic information for the entire population, to the block level. SF2 contains similar information, detailed for ethnic subgroups, American Indian and Alaska Native tribes, and multiple-race individuals. These data are suppressed when the total number of individuals in a given geographic unit totals fewer than 100. SF3 contains detailed housing, demographic, and socioeconomic data to the census block group or census tract level, based on a long form that was sent to one in six households. Census block groups have an optimal population size of 1,500 and census tracts have an optimal population size of 4,000, though in practice populations vary widely. SF4 contains the same information as SF3 for detailed race and ethnic groups, with the same suppression rule as SF2. In addition to these four primary data files, the Census Bureau also provides digital cartographic boundary files for political entities in the country, as well as approximations of postal code boundaries known as ZIP code tabulation areas (ZCTAs).The Census Bureau also conducts the American Community Survey (ACS), an ongoing survey designed to reach 3 million households each year nationwide. The goal of this survey is to allow the publication of detailed demographic and socioeconomic information more often than once a decade. Data for geographic units totaling more than 65,000 people will be released annually, while data for smaller geographic units will be based on either a three or five year moving average. It will replace the census long form, which will not be administered in 2010. There will undoubtedly be a challenging adjustment period as public health researchers begin to use ACS data.At present, the level of information available for intercensal time points is quite limited, and derives from Census Bureau estimates at the state or county level. These estimates are used in the calculation of cancer rates by federal and state agencies, although some research has shown that they are not especially reliable, particularly county-level estimates for specific race groups . VariousThe 2000 census allowed respondents to select more than one race, although cancer data are only beginning to be collected in this manner. As a result, population data from 2000 must be "bridged" back to the earlier single-race categories to allow comparisons with earlier data. NCHS developed a sophisticated bridging algorithm taking into account age, sex, distribution of single-race groups within counties, and other covariates . This alIn addition to the issues noted above, it is important to realize that even the decennial census counts are not as accurate as popularly believed. The census represents an attempt to enumerate the population as of a single date, but invariably some people are missed or double-counted. These undercounts and overcounts are differential by race, socioeconomic status, and geographic area, potentially biasing cancer rates ,57.Countless epidemiologic and geographic studies make use of census data in some capacity, including most studies that report cancer rates for geographic areas. It is also quite common to use census data where individual-level data are not available, particularly for indicators of socioeconomic status -60, educ.In addition to the Census Bureau as a primary source of sociodemographic attribute data, special survey data can provide valuable information on these characteristics for population groups in some areas. Perhaps one of the best known such surveys is the CDC-sponsored Behavioral Risk Factor Surveillance System (BRFSS), which is touted as the "world's largest telephone survey". Designed in the 1980s to track trends in behavioral risk factors at the state level, this ongoing system of national surveys also provides subarea and subgroup information within some of the larger states. Some researchers have estimated county-level behavioral risk factor prevalence by combining the statewide BRFSS data with county-level demographic data ,63. A maAnother well-known national survey is the NCHS's National Health and Nutrition Examination Survey (NHANES), which has been in place since 1960 and combines questionnaire information with a national physical examination and biomonitoring program. NCHS also sponsors a National Health Care Survey (NHCS), a National Health Interview Survey (NHIS), a National Immunization Survey (NIS), and a National Survey of Family Growth (NSFG). Similarly designed large-scale efforts to track temporal and area differences for targeted health behaviors within a state include California's Tobacco Survey, Women's Health Survey, and Health Information Survey Table .Although population survey data has not been extensively incorporated into GIS studies to date, these resources may in the future provide some opportunity to characterize regional differences in behavioral risk profiles targeted for specific health outcomes., the Environmental Protection Agency (EPA) National Air Toxics Assessment database , and EPA's Toxic Release Inventory program . EPA has organized environmental data in an umbrella database called Envirofacts Data Warehouse . Some states have extensive efforts to collect additional environmental data. An example is California's Pesticide Use Reporting program ) that requires reporting of all agricultural pesticide use at the level of Public Land Survey System sections (a unit approximately one square mile in area).Over the past several decades there has been a large increase in the availability of spatially registered environmental data in the United States and other countries. Much of these data have been collected as a result of environmental regulations or government-funded research efforts. Examples of US programs to collect spatial data on concentrations or releases of pollutants in the environment include the United States Geological Survey (USGS) National Assessment of Water Quality program (NAWQA) There are several issues to consider in using these data for assigning "exposure" in epidemiologic studies. Monitoring data collected for regulatory purposes should be carefully evaluated for its usefulness for estimating individual exposures. The fate and transport of the chemicals in the environment should also be considered. Simple proximity measures to sites of chemical releases may not adequately describe the transport of the chemical in the environment. The likely route of exposure should be considered along with the biological plausibility for an association between the exposure and disease under study. Finally, much of the environmental monitoring data was collected within the past decade and reconstructing exposure over longer periods more relevant to cancer incidence will be challenging.Environmental databases have begun to be used in epidemiology studies of cancer to determine if disease mortality or incidence rates are higher in areas with specific environmental exposures (i.e., ecologic study designs) or as a means of classifying individuals with respect to their potential exposure in an analytic epidemiologic study design (i.e., case-control, cohort studies). With few exceptions, the residence location is used as the geographic location for assigning exposure. Below we provide an overview of the various types of spatially registered exposure data and include examples of their use in epidemiologic studies of cancer.The US EPA is responsible for regulating public drinking water supplies. A water supply is regulated if it has 5 or more connections or serves at least 25 people. Routine monitoring is required for a variety of contaminants and naturally occurring elements including disinfection by-products, arsenic, nitrate, certain pesticides and volatile organic chemicals. States are required to report violations of the Maximum Contaminant Levels (MCL) to EPA. Since 1996, EPA has been required to maintain a National Contaminant Occurrence Database (NCOD) using occurrence data for both regulated and unregulated contaminants in public water systems. The majority of historical public water supply measurement data, however, reside with the states. Some states record the latitude and longitude of the locations where the water samples were taken (location in the distribution system, point of entry to the distribution system, or water source location). The location information is typically not publicly available but may be available to researchers with appropriate approvals.The water quality data are reported by utility and to be useful for epidemiologic studies a linkage to the towns served must be established. In larger metropolitan areas multiple utilities may serve a city or, conversely, one utility may serve multiple towns and subdivisions. Therefore, establishing an accurate linkage between the study participant's addresses and water utilities is essential to avoid misclassification of exposure. Long-term exposure metrics can be calculated when a lifetime water source history is collected. Examples of studies using public supply water quality monitoring data include studies of disinfection by-products -66., nit. The paucity of historical water quality data for private wells limits the exposure assessment for epidemiologic studies of cancer in this population.In contrast to public water supplies, private domestic wells are not regulated and there are no monitoring requirements, although well owners may be required to provide some water quality information upon the sale of a property in some states. Some states have conducted representative surveys of private well water quality . A natioThe USGS NAWQA program has been collecting information on nutrients, pesticides, volatile organic compounds, radionuclides, and major ions in more than 50 river basins and aquifers since 1991. All of the measurement data include spatial attributes. Because the goal of this research effort is to understand ambient water quality  these data may not be of direct use in epidemiologic studies. However, the NAWQA data may be useful in modeling efforts to estimate contaminant levels in private wells. EPA also maintains two data management systems containing water quality information collected by federal, state, and private groups for surface and ground waters in all 50 states. The Legacy Data Center (LDC) is an archived database with data dating from the early 20th century up to the end of 1998. STORET contains data collected beginning in 1999, along with older data documented data from the LDC. Table The EPA collects and processes monitoring data from states on six criteria air pollutants (carbon monoxide, nitrogen dioxide, ozone, sulfur dioxide, particulate matter [PM10 and PM2.5], lead) and hazardous air pollutants, of which 188 have been identified. The hazardous air pollutants (HAP), also known as air toxics, are those for which there is some evidence of an increased risk for cancer or adverse reproductive outcomes. Routine monitoring of HAPs is not required and the monitoring data that exists is sparsely distributed compared with the criteria air pollutants. The data are maintained in the Air Quality Systems database.EPA compiles HAP emissions from stationary sources (points and areas) and mobile sources in a National Toxics Inventory (NTI) database , which is updated at three-year intervals. To do the updates, EPA obtains emissions inventories from state environmental agencies and supplemental data from other sources, including the Toxic Release Inventory. The first nationwide inventory was in 1996. The spatial scale of the emissions data varies by type of source. Location information for point sources emissions is available, whereas area-source emissions are estimated at the county level. Using a dispersion model EPA has estimated the annual average HAP concentrations for each census tract in the contiguous US . These dAir pollutant monitoring data has been used in studies of lung cancer, which have generally employed some type of dispersion model to estimate exposure for metropolitan areas or census tracts -81. ReceIn the United States the U.S. Department of Agriculture (USDA) is the main federal agency responsible for collecting information on pesticide use on crops and livestock. The availability of historical agricultural pesticide use data in the US has been reviewed . The firSeveral states have collected their own pesticide use information but most data collection efforts have been recent. Oregon enacted legislation requiring reporting of agricultural pesticide use beginning in 2002; however, insufficient funding was provided for additional years. State pesticide use data are most comprehensive for California, which has had some type of mandatory reporting for agricultural pesticides since the 1950s, currently overseen by the California Department of Pesticide Regulation. Beginning in 1969, information about restricted-use pesticides was made public. In 1990, a new law required growers to report all pesticide use on crops on a monthly basis, including the pesticide name and manufacturer, crop treated, the public land survey section where the pesticide was applied, the date and time of application, number of acres treated, method of application, and application rates. The availability of this detailed pesticide use data at the spatial scale of a section led to the development of methods to link the use data to cancer incidence data  for use The Emergency Planning and Community Right to Know Act of 1986 in the United States requires certain industries to report to EPA annually their releases and waste management activities involving specific toxic chemicals. The data are available to the public in a database called the Toxics Release Inventory (TRI). Manufacturing, metal mining, coal mining, and electric generating facilities must report the estimated mass of toxic chemicals released into the environment (air, water, land, or underground injection), treated on-site, or shipped off-site for further waste treatment. Reporting is required only for facilities that meet certain minimum criteria in terms of the pounds of toxic chemical produced or processed; persistent chemicals that bioaccumulate are subject to lower minimum reporting requirements. The regulations do not require environmental monitoring, so much of the data are estimates of releases. Location information is reported by the business and is not verified by EPA. Some of the strengths and limitations of these data for environmental health studies has been described ,89.Canada also requires reporting of emissions of chemicals rated by the International Agency for Research on Cancer as likely, probable, and possible human carcinogens for 64 industrial sectors . These dThe EPA maintains information on the location of waste handlers, waste treatment facilities and waste sites that are regulated under the Resource and Conservation Recovery Act (RCRA) and the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), also known as the Superfund law in the RCRAInfo database available through the Envirofacts Data Warehouse. Information on the location of companies issued permits to discharge waste into rivers is maintained in the Permit Compliance System database . These data sources are summarized in Table The U.S. Agency for Toxic Substances and Disease Registry (ATSDR) was established by Congress in 1980 under CERCLA. Since 1986, ATSDR has been required to conduct a public health assessment at each of the sites on the EPA National Priorities List, waste sites deemed to be the most hazardous. The aim of these evaluations is evaluate exposure to hazardous substances and health effects among the population living in vicinity of the site . The locThe reconstruction of historical exposure to releases from industries and waste sites is difficult for studies of cancers of long latency. A few studies have evaluated proximity and residence duration near sites. Long duration of residence within one-half mile of a chemical plant manufacturing PCBs was positively correlated with blood serum PCB concentrations . HoweverRemotely sensed data include images of the earth and our atmosphere obtained by satellites or aircraft. The usefulness of the information depends largely on the technology used to obtain the imagery and the additional processing that has been done to georeference the data. The USGS Earth Resources Observation Systems Data Center (EDC) is the major U.S. storehouse of these data. Aerial photography has been available since the early part of the twentieth century. Digital Orthophoto Quadrangles (DOQs) which are digital images of aerial photos which combine the image characteristics of a photo with the georeferenced qualities of a map are available through EDC from 1987 through the present. DOQs are available in black and white, natural color, or color-infrared images and have 1-meter ground resolution. Satellite imagery useful for land cover characterization includes the multispectral Landsat imagery available as early as 1972. USGS has created historical land use and land cover data derived from 1970s and 1980s aerial photography (the Land Use and Land Cover Data). A national land cover datasets (NLCD) derived from Landsat multispectral imagery for 1992 is available. The Multi-resolution Land Characteristics (MRLC) national dataset which represents land cover in 2000 is currently being developed. Table  offers links to many of these sources, as well as links to freely available geographical tools and resources. There have also been several initiatives to try and compile spatial data into a shared, centralized information system [. The FGDC is a consortium of federal agencies with the charge of developing the National Spatial Data Infrastructure (NSDI), a set of technologies, policies, standards and procedures that facilitate the creation and sharing of geospatial data. Among the achievements of the FGDC is the establishment of the National Spatial Data Clearinghouse, a central catalog of links to geospatial data and metadata. In 2003, an enhanced web portal  was launched to further facilitate access to this data. Many states have echoed the national clearinghouse with clearinghouses of their own. The New York GIS Clearinghouse , for example, boasts over 400 member institutions providing links to thousands of datasets.The data sources we have described are available from a multitude of federal and state agencies. The National Cancer Institute's Geographic Information Systems web site n system . Such ce. Most of the very limited data in the "human health and disease" category accessible through the web portal consisted of hospital and other health facility locations for a smattering of states. In some cases, the steps required to make cancer data available through the national clearinghouse would be modest. For example, the NCI's mortality data, geographic boundary files, and associated metadata used in its Cancer Mortality Maps and Graphs web site are easily accessed and downloaded, and only minor modifications would be required to make them compliant with FGDC standards.The cancer data collection community has yet to fully engage this resource. As of January 2004, no cancer incidence or mortality data was available through the national clearinghouse. The keyword "cancer" provided only a link to the Environmental Defense Scorecard, a web site from which various environmental data sets can be accessed, particularly those published by the EPA  is another centralized online data resource, consisting of a network of online data libraries created in a collaboration between the CDC and the US Census Bureau. The libraries consist of both microdata and aggregate data in numerous categories. Available health data includes NHANES and NHIS survey data and county-level mortality. Information in DataWeb is accessed through DataFerret, an application that prepares data sets for the user to download. It allows users to select a "databasket" of variables and then recode those variables as needed. Users develop and customize data tables and may download them to their desktop in a variety of common formats.The DataWeb In this article we have surveyed the distinctive characteristics of spatial data, along with commonly available sources of data relevant to etiologic cancer research. Spatial analysis is invaluable for data exploration, identification of geographic patterns, generation of new hypotheses, and providing supporting evidence about existing hypotheses. A geographic perspective will be increasingly relevant as GIS software, spatial analytic methods, and the availability and quality of geographically referenced data continues to improve.


The feasibility of drug monitoring of serum concentrations of morphine, morphine-6-glucuronide (M6G) and morphine-3-glucuronide (M3G) during chronic morphine therapy is not established. One important factor relevant to drug monitoring is to what extent morphine, M6G and M3G serum concentrations fluctuate during stable morphine treatment.We included twenty-nine patients admitted to a palliative care unit receiving oral morphine (n = 19) or continuous subcutaneous (sc) morphine infusions (n = 10). Serum concentrations of morphine, M6G and M3G were obtained at the same time on four consecutive days. If readmitted, the patients were followed for another trial period. Day-to-day variations in serum concentrations and ratios were determined by estimating the percent coefficient of variation (CV = (mean/SD) ×100).The patients' median morphine doses were 90  mg/24 h and 135  mg/24 h during oral and sc administration, respectively. Intraindividual fluctuations of serum concentrations estimated by median coefficients of day-to-day variation were in the oral group for morphine 46%, for M6G 25% and for M3G 18%. The median coefficients of variation were lower in patients receiving continuous sc morphine infusions (morphine 10%, M6G 13%, M3G 9%).These findings indicate that serum concentrations of morphine and morphine metabolites fluctuate. The fluctuations found in our study are not explained by changes in morphine doses, administration of other drugs or by time for collection of blood samples. As expected the day-to-day variation was lower in patients receiving continuous sc morphine infusions compared with patients receiving oral morphine. Morphine is degraded in the liver to several metabolites of which morphine-6-glucuronide (M6G) and morphine-3-glucuronide (M3G) are biological active . M6G is The most obvious determinants for serum concentrations of morphine, M6G and M3G are morphine doses, route of administration and renal function. However, a considerable variation of serum concentrations between patients remains after correcting for dose and route of administration -13.Measurements of morphine, M3G and M6G serum concentrations can explain individual responses in patients where morphine treatment turns out to have unexpected effects and help physicians to determine changes in pain treatment. Physicians tend to believe that samples obtained for therapeutic drug monitoring during steady state conditions will be representative irrespective of which day the sample is collected. However, morphine, M6G and M3G serum concentrations may also have fluctuations not caused by changes in morphine doses, administration of other drugs or by time for collection of blood samples. This variation represents the day-to-day variability. In order to evaluate the clinical implications from morphine and metabolites serum concentrations measurements it is necessary to know if these serum concentrations have fluctuations not related to changes in drug administrations.The day-to-day variability in serum concentrations of morphine, M6G and M3G are previously reported in a study of 8 cancer patients treated with subcutaneous (sc) morphine infusions. This study observed coefficients of variation (CV) ranging from 26%–56% for morphine, 20% to 51% for M6G and 20%–49% for M3G . To our Thus, the aim of this study is to investigate the day-to-day variations of morphine, M6G and M3G serum concentrations during stable chronic oral and sc morphine administration to cancer patients.We included twenty-nine patients admitted during a nine-month period to the Palliative Care Unit at the University Hospital in Trondheim. The inclusion criteria were; verified malignant disease, expected survival time less than 6 months, scheduled morphine treatment started at least three days prior to inclusion, stable scheduled doses of morphine for a minimum of three days and age more than eighteen years. The exclusion criteria were; planned hospitalisation less than three days and lack of ability to communicate (e.g. dementia, deafness).All patients gave their written informed consent before inclusion. The study was conducted according to the guidelines of the Helsinki declaration. The Regional Committee for Medical Research Ethics, Health Region IV, Norway, approved the study.The patients were included in the study within three days after admission to the Palliative Care Unit. Each patient was followed for four days. Patients readmitted to the Palliative Care Unit were allowed to a new trial period identical to the first trial period. No patients were included in more than three trial periods.The patients' age, gender, primary malignant diagnosis, presence of metastasis, and other medications were registered. Morphine treatment during the last 24 hours was registered with respect to route of administration, morphine formulation, scheduled dose and consumption of rescue morphine for breakthrough pain. The patients' functional status was assessed using the Karnofsky performance status score .Blood samples were obtained each day during the trial period. The samples were obtained at the same time each day during the routine morning round for collecting blood samples.In order to observe if the patients were studied during stable treatment conditions the scheduled morphine dose, rescue morphine consumption and route of administration were registered each study day. The use of other medications was also registered daily. Pain, nausea and sedation were assessed at day study two, three and four during the trial period using a 5 category verbal rating scale (VRS) score ranging from no to very severe. All symptoms were assessed for the last 24 h.Analytical) were for morphine 3,0%, for M6G 5,5% and for M3G 7,0%. The analytical coefficients of variation were determined at 100 nmol/l for morphine and 1000 nmol/l for M6G and M3G. Serum values of creatinine concentrations, alanin aminotransferase activities (ALAT), aspartat aminotransferase activities (ASAT) and albumin concentrations were determined using standard analytical methods.The blood samples were placed in EDTA tubes until separated by centrifugation (3000 rpm, ten minutes) and stored at -85°C until analysed. All samples were analysed for serum concentrations of morphine, M6G and M3G applying liquid chromatography mass spectrometry . The limTotal use of morphine for each trial day was calculated by adding scheduled morphine doses and rescue morphine consumption. Samples obtained less than two hour after the administration of a morphine rescue dose were excluded from the analyses.Biological), expressed in terms of percent coefficient of variation, was calculated for each patient in each trial period using the equation [Day-to-day variations of morphine and its metabolites are presented as biological coeffecients of variation. This biological variation  for morphine, M6G and M3G, which represent the variation in serum concentrations for each patient during each trial period, were calculated using the equation [The observed coefficients of variation  median age at inclusion was 68 years . The patients' Karnofsky performance status, primary tumor diagnoses and presence of metastases are shown in Table Ten patients used non-opioid analgesics . The patients used a median number of 5 range; 1–10) non-pain medications. The numbers of patients using psychotropic drugs, antiemetics or corticosteroids are given in Table –10 non-pOf the nineteen patients receiving oral morphine sixteen patients completed one trial period, two patients completed two trial periods and one patient completed three trial periods. The corresponding numbers for the ten patients receiving sc morphine were four, five and one, respectively. Six patients were excluded during a study period. The reasons were; discharge from hospital (n = 2), opioid treatment changed to fentanyl patch (n = 1) and fatigue (n = 3). Opioid induced adverse effects caused no exclusions. Sixteen blood samples were not obtained due to circumstances related to the patients' or relatives' needs (e.g. visits from relatives at the time of a planned blood sample).The median duration of morphine treatment before entering the study was 7 months . The median morphine dose at inclusion for the patients receiving oral treatment (controlled-release morphine) was 90 mg/24 h . The median morphine dose for the patients receiving sc morphine infusions was 135 mg/24 h . The morphine doses varied between the study days because the patients were allowed to use rescue morphine. This variation, however, was minor  for morphine serum concentrations was 46%  during oral morphine therapy and 10%  during sc morphine infusions Table . The medIntraindividual fluctuation of drug serum concentrations not explained by changes in doses, administration of other drugs or by time for collection of blood samples, is the day-to-day variation. Routine measurements of serum concentrations of morphine and metabolites are of questionable value because of the large variability of minimum effective serum concentration and the lack of a direct relationship between serum concentrations and adverse effects . Howeveret al. reported day-to-day variations during morphine treatment in eight cancer patients receiving continuous sc morphine infusion for 1 to 23 weeks. The individual CV values observed in their study varied between 26% to 56% for morphine, 20% to 51% for M6G and 20% to 49% for M3G [The available data on day-to-day variability during chronic morphine treatment is sparse. Vermeire  for M3G .et al.. One explanation for this discrepancy is that Vermeire et al. obtained blood samples during treatment periods up to 23 weeks. This study design may overestimate day-to-day variability since patient related factors will vary more during long time intervals than between consecutive days.We observed less day-to-day variations of morphine and metabolites concentrations during sc morphine treatment (morphine 10%, M6G 13%, M3G 9%) compared to the fluctuations reported by Vermeire To our knowledge this is the first study to assess the day-to-day variation of morphine and morphine metabolites serum concentrations during oral morphine therapy. The median observed CV values for serum concentrations of morphine, M6G and M3G during oral morphine therapy (morphine 46%, M6G 25%, M3G 18%) were higher than the CV values observed in patients receiving sc morphine treatment (morphine 10%, M6G 13%, M3G 9%). This observation was expected due to a more stable delivery rate and since absorption during sc administration is not influenced by food intake, gastric retention, malabsorption, vomiting or variable first-pass metabolism.et al., represent day-to-day variability in cancer patients admitted to a palliative care unit. In this patient population pharmacological observations will be influenced by variations in food intake, gastric retention, malabsorption, effects from other drugs on gastric emptying, vomiting and drug interactions. In order to perform a study on day-to-day variation not suspect to these confounding factors patients or volunteers must be recruited into a controlled experimental environment. We believe that studies in controlled experimental environments and studies in patients with advanced cancer disease are complementary to each other. The first targets the pharmacokinetic phenomenon of day-to-day fluctuations, the second targets the fluctuations met during clinical real-life conditions.The results in our study, as in the study by Vermeire We recognise some limitations in our study. First, blood samples were collected during four trial days. An extended trial period in order to obtain a larger number of samples from each patient gives a more precise estimate of day-to-day variation. However, due to ethical considerations, taking into account the strain on each patient from serial blood sampling, we chose to not extend the trial periods beyond four days. A second potential confounding factor is absorption peaks in serum concentrations caused by rescue doses of morphine. We chose to allow for rescue morphine because we wanted to observe the variability of serum concentrations as observed in a normal clinical setting in patients considered to be clinical stable in respect to pain treatment. We belive that the variability caused by serum concentration peaks is limited since samples obtained within a time interval of two hours after administration of a morphine rescue dose were excluded. However, it is important to recognize that in order to observe the exact pharmacological day-to-day variability of serum concentrations of morphine and morphine metabolites a design with a stable baseline morphine dose and a non-morphine alternative for breakthrough pain should be applied. Third, the use of rescue morphine implies that the daily morphine doses were not constant. However, the small changes in daily morphine doses can not explain the observed day-to-day variability.In this study we assessed clinical symptoms related to opioid treatment in order to verify the stable intensities of symptoms during the study period. We did not attempt to explore the relationships between serum concentrations and clinical outcome measures. As a rule of thumb 25 patients are required per independent variable in order to give valid results in studies exploring the effects from factors predicting clinical observations . ConsequMorphine, M6G and M3G serum concentrations vary considerably in samples obtained on consecutive days. Such variability is present during stable morphine doses and stable clinical symptoms. The day-to-day variability was lower in patients receiving continuous sc morphine infusions compared with patients receiving oral morphine. These findings indicate that results from blood samples taken in order to assess a patient's pharmacological morphine status should be interpreted with the understanding of that variability is partly caused by day-to-day variation.The authors declare that they have no competing interests.PK, PH and JM participated in the design of the study, running of the study and preparation of the manuscript. SK, PCB and OD participated in the design of the study and preparation of the manuscript. KZ was responsible for measurements of morphine and morphine metabolite serum concentrations.The pre-publication history for this paper can be accessed here: