To systematically review, critically appraise the quality of recent clinical practice guidelines (CPGs) for neonatal hypoxic ischemic encephalopathy (HIE), and map their recommendations.CPG databases , Bibliographic databases , and related specialized professional societies .Original de-novo developed evidence-based CPGs for HIE, group authorship, Arabic or English languages, and international or national scope. The systematic review was drafted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement and Johnston et al methodological guide.Quality assessment of the included HIE CPGs by the Appraisal of Guidelines for REsearch & Evaluation II (AGREE II) Instrument and report their characteristics, AGREE II ratings, and recommendationsOur search retrieved 2,489 citations, of which two recent HIE CPGs were eligible and appraised: Canadian Paediatric Society (CPS) and Queensland Maternity and Neonatal Services (QMN). The overall assessment of the QMN CPG was superior (83%). Domain 1 (Scope & Purpose) scored , Domain 2 (Stakeholder Involvement) , Domain 3 (Rigour of Development) , Domain 4 (Clarity & Presentation) , Domain 5 (Applicability) , and Domain 6   for the QMN and CPS CPGs respectively. All appraisers recommended the QMN CPG for use in practice.The methodological quality of the QMN CPG was superior with the relevant recommendations for its use in neonatal practice.limited to Arabic and English languages.https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=258291, identifier: CRD42021258291. Survivors of hypoxic-ischemic encephalopathy (HIE) have shown reduced neuropsychological functioning, behavioral adjustment, and school outcomes during adolescence among other neonatal morbidities, mortalities, and outcomes .Several initiatives were launched to promote and advance evidence-based neonatal healthcare by national  and international organizations and professional societies  .Despite the emphasized potential of Clinical Practice Guidelines (CPGs) to optimize patient outcomes and clinical practice, an increasing volume of CPGs is being published of variable quality in the field of neonatology –5.In 2012, The Saudi Neonatology Society (SNS) published a CPG for Whole Body Cooling for infants with HIE . The SNSThe systematic review (SR) and quality appraisal of CPGs using the Appraisal of Guidelines for REsearch & Evaluation II (AGREE II) Instrument is a critical step in the KSU-Modified-ADAPTE CPG adaptation process , 13.PREPARE (Practice guideline REgistration for trancPAREncy) platform that is hosted by the University of Lanzhou in China http://www.guidelines-registry.org/ (Registration Number: IPGRP-2021CN384) (The overarching CPG adaptation project was registered in the 21CN384) .This study aimed to report the systematic review and quality assessment of HIE CPGs as a part of the HIE CPG adaptation process.The protocol for this systematic review of CPGs was registered in PROSPERO  (ID: CRD42021258291) . This syOur Guidelines Review Group (GRG) included seven expert consultant neonatologists: one of them with expertise in systematic reviews, two consultant Obstetricians and Gynecologists, a senior nurse, a medical and healthcare librarian, and a CPG methodologist with a background in pediatrics.The medical librarian systematically searched MEDLINE, EMBASE, and CINAHL databases for relevant CPGs using the Ovid platform and hand-searched the relevant CPG databases and repositories for eligible CPGs .Two reviewers (MA and OE) conducted the title and abstract screening of the CPGs and articles independently. Two different reviewers double-checked the full-text screening (YSA and JA) and disagreements were resolved through focus group discussions. The full inclusion and exclusion criteria were reported in the PROSPERO protocol . The seawww.agreetrust.org) has 23 items or questions divided into six domains: scope and purpose, stakeholder involvement, rigor of development, clarity of presentation, applicability, and editorial independence. Using a 7-point Likert scale, each item was scored using its online platform (My AGREE PLUS). Each CPG was critically appraised by four AGREE II raters including four clinicians, and one of them was a CPG methodologist . We did this by utilizing a percent agreement inter-rater reliability assessment test. The consistency of ratings or the capacity for datasets that were gathered as clusters or sorted into clusters using intra-class correlation were also assessed in the second overall assessment (OA2) in addition to the percent agreement in the first overall evaluation (OA1). One common IRR strategy is intra-class correlation (ICC).When there are more than two raters, we use this. Standards from the same set appeared to be fairly comparable, as shown by a strong intra-class correlation coefficient (kappa) around 1. A low kappa score near 0 denoted a lack of similarity between standards from the same collection. Since our raters and rates varied, we used ANOVA “One-Way Random” on SPSS Statistics, version 21. The extensive range of numerical data from groups or clusters is why we chose ICCC. This allowed us to assess the repeatability and the degree to which peers shared particular characteristics. We looked at how well two categories on an ordinal scale agreed with one another.Given that the data originated from an ordered scale, we employed weighted kappa (quadratic weights). Following are the weights' calculations: The notation is Cohen's kappa. We decided on linear weights because the difference between the first and second categories was similar to the difference between the second and third categories, and so on. The kappa (K) statistic is used to measure agreement , 19: Whehttps://www.rayyan.ai/ only two source original CPGs were found to be eligible for the AGREE II quality assessment step. Two reviewers conducted the screening  and two additional reviewers  resolved any discrepancies through discussions  scored  respectively in domain 1 where the CPS CPG reported its objectives, health questions, and patient population more clearly addressing most of the AGREE II criteria and additional considerations.CPS and QMN CPGs scored 39% and 72% respectively, where the QMN CPG development group was properly reported and included a multidisciplinary team representing all related specialties to neonatal HIE.CPS and QMN scored 43% and 48% respectively. There was a large area for improvement in both CPGs in properly and clearly reporting the search methods, evidence selection criteria, strengths and limitations of the evidence, formulation of recommendations, consideration of benefits and harms, link between recommendations and evidence, external review, and updating procedure. Both CPGs reported an overall process of their CPG development the aforementioned criteria need to be reported transparently in clear detail to facilitate the replication of the CPG development process. Both CPGs have not reported using the GRADE  Method.CPS and QMN CPGs scored 96% and 100% in domain 4 respectively. Both CPGs presented specific and unambiguous recommendations, comprehensive management options, and a set of identifiable key recommendations.CPS and QMN CPGs scored 9% and 59% in domain 4 respectively. The QMN CPG was superior in its variable set of CPG implementation tools inside the CPG article or on the website including management flowcharts and posters, points for discussion with the parents, checklist for therapeutic hypothermia, assessment of encephalopathy severity (Sarnat scoring), Sarnat and Sarnat staging of HIE, educational material, and patient information on HIE.CPS and QMN CPGs scored 17% and 67% respectively where QMN CPG documented the funding body and the conflicts of interest more clearly.The AGREE II standardized domain scores for the first overall assessment was higher for the QMN CPG (83%) than the CPS CPG (63%).The second overall assessment revealed a consensus between the four reviewers on recommending the use of the QMN CPG while half of the reviewers recommended using the CPS CPG and half of them recommended its use with modifications.In terms of Classification of the strength of agreement among the four raters against the two guidelines; the assessment was classified according to strength into Poor, Fair, Good, Very Good, and Excellent. With an emphasis on the sum of scores, the sum of OA scores, and the first overall assessment. Regarding the CPS 2018 Position Statement; it was arranged as follows; 0, 0, 12, 6, 6, 333, and 19 however, QMNCG 2021 Queensland Maternity and Neonatal Clinical Guideline was 0, 0, 2, 6, 16, 431 and 24. The difficulty of variation in their quality and evidence base continues despite the significant volume of national and international neonatal CPGs that are regularly released. To our knowledge, this evaluation is unique in that it uses AGREE II to comprehensively assess the quality of recently published HIE CPGs as a part of a nationwide CPG adaptation program .The methodological rigor of the two HIE CPGs was evaluated using the AGREE II instrument, which identified a number of opportunities for improvement. Although the evaluation of the overall guideline quality and the usage of the recommendation are essential sections of AGREE II, it's likely that they are not clearly communicated in the published CPGs' methodology.A recently published network meta-analysis compared the effectiveness and safety of different neuroprotective interventions for neonates with HIE . This stShipley et al. emphasized the importance of training, equipping, and supporting neonatal centers that lack immediate access to cooling services with active therapeutic hypothermia should be prioritized, reducing interruptions in initiating and achieving appropriate target temperature before transfer to specialized tertiary cooling neonatal centers .We continue to recommend compiling the findings of this study with similar quality appraisals of neonatology CPGs to set up a CPGs hub or Recommendation map that would be of the utmost value for healthcare providers caring for newborn babies in selecting and implementing high-quality evidence-based CPGs and recommending them to their colleagues , 25–29.Moreover, we are looking forward to having new evidence-based recommendations in the next editions of these CPGs based on the mounting evidence addressing the new options of care like the use of conventional electroencephalography (EEG) or Amplitude-integrated Electroencephalogram (aEEG) monitoring in neonatal HIE , 31.The findings of our review can be further used to guide all relevant CPG development or adaptation project for neonatal HIE.Implementation of the results of this systematic review through identifying and selecting high-quality CPGs will decrease variation in the management of neonatal HIE babies which might lead to improved clinical outcomes and decrease legal litigations.We recommend monitoring the implementation of the process and auditing the process for quality improvement. Reporting adverse outcomes or variance of practice might help for future updates.The methodological quality of the QMN CPG was superior followed by CPS. Recommendations addressed inclusion and exclusion criteria, fluid management, feeding, resuscitation, anticonvulsant drugs, sedation, allopurinol, xenon, melatonin, erythropoietin, neural stem cells, erythropoietin, magnesium sulphate, therapeutic hypothermia and target temperature, rewarming, brain MRI timing, and follow up.


BackgroundMiscarriage is one of the common problems encountered in pregnancy. The treatment modalities are expectant, medical, and surgical management. This study compared the effectiveness and safety of manual vacuum aspiration (MVA) with expectant management for first trimester miscarriage.MethodThis randomized controlled trial was conducted in Teaching Hospital Jaffna, Jaffna, Sri Lanka, and 134 eligible patients with first trimester spontaneous miscarriage were randomized to expectant management (67) and MVA (67). Those allocated to expectant management were managed expectantly for up to two weeks, and those allocated to MVA underwent aspiration under a paracervical block in the ward. The primary outcome was complete evacuation of the uterus, and the secondary outcomes were duration of bleeding, duration of pain, level of pain, need for the second procedure, cervical or uterine injuries, and patient satisfaction.ResultsOf the 134 eligible women, seven were lost to follow-up and 127 were analyzed. The MVA was superior in achieving complete evacuation compared to expectant management . Notably, in both groups, complete evacuation was more readily achievable in incomplete miscarriage than in missed miscarriage. Duration of bleeding , duration of pain , and the need for additional surgical procedure in the form of dilatation and curettage  were lower in MVA. Patient satisfaction was higher in the MVA group than in the expectant group . No statistically significant differences were observed between the groups in terms of blood transfusion and infection. There wasn’t any incidence of cervical damage or uterine perforation.ConclusionMVA is an effective and safe treatment method for first trimester miscarriage with higher patient satisfaction. Miscarriage is a common event that can occur in any pregnancy and is seen in approximately 30% of all pregnancies . Early fFor the treatment of miscarriage, different modalities, such as expectant, medical, and surgical management, have been practiced worldwide. Expectant management denotes allowing some time for the natural expulsion of products without intervention. During this time, the patient may require rest, USS, and prophylactic antibacterial drugs to prevent infections. In studies done in the past, the success rate of expectant management varied from 58% to 80%, and complete evacuation of the product of conception was achieved within two weeks of recognition with minimal infection incidence -6. ThougIn Sri Lanka, though DNC and electric vacuum suction have been widely practiced as a surgical treatment for miscarriage, MVA has not been routinely practiced. In Sri Lanka, there haven’t been any studies comparing the effectiveness of MVA against other methods as a treatment of choice for early pregnancy demise. In most of the studies that assessed the treatment methods of miscarriage, the surgical technique was found to be the traditional DNC ,17. We cThis randomized control trial was done in the obstetrics and gynecology ward in Teaching Hospital Jaffna, Jaffna, Sri Lanka, from January 2017 to January 2018. Ethical clearance was granted by the ethical review committee of the Faculty of Medicine, University of Jaffna, Jaffna, Sri Lanka. This trial was prospectively registered in the Sri Lanka Clinical Trials Registry (SLCTR/2017/014). The inclusion criteria of the study were as follows: pregnant women with the diagnosis of miscarriage presented with ≤12 weeks of gestation, hemodynamic stability, temperature not greater than 37.5°C, age 18 years or older, no history of using anticoagulants or steroids, and absence of significant medical or surgical conditions. Women diagnosed with pelvic infections, ectopic pregnancy, and bleeding disorders were excluded from the study. From the sample size calculation using 80% power, this trial required a sample of 62 in each arm, according to the anticipated loss (10%) of follow-up. A total of 152 participants were screened for eligibility, and 18 were excluded due to declining participation (16) and a history of pelvic infection (two). In all, 67 were allocated to each arm from the 134 eligible patients, and 127 were analyzed, as seven were lost to follow-up  for four hours was considered a fever, and severe abdominal pain was considered a scale of 8-10 in the visual analog score (VAS). During the follow-up visits, all women were assessed clinically in view of complete evacuation and complications and underwent transvaginal ultrasound regardless of clinical findings. The same experienced medical officer performed all the transvaginal scans.Women in the expectant management arm were allowed home after the initial assessment with symptoms check sheets, and they were instructed to return to the hospital if they developed any heavy vaginal bleeding, fever, or severe abdominal pain before the scheduled follow-up visits at days 7 and 14 in gynecology outpatient clinic or ward. They were advised to take paracetamol for the pain, on a demand basis.Women allocated an MVA arm were given a stat dose of oral antibiotics (azithromycin 1 g), paracetamol (1 g), and ibuprofen (400 mg) one hour before the procedure. Rhesus negative women were administered anti-D prophylaxis. Registrars and senior medical officers who have prior experience in MVA performed the procedure, which was done under the paracervical block with 2% lignocaine using a handheld MVA pump. Patients were observed for six hours post-procedure and discharged home if hemodynamically stable. They were instructed to return to the hospital if they developed any heavy vaginal bleeding, fever, or severe abdominal pain before the scheduled follow-up visit one-week post-procedure in the gynecology outpatient clinic or ward. The primary outcome of the research was the rate of complete emptying of the uterus. The completeness was defined as an empty uterus with an endometrial thickness below 15 mm calculated in the anterior-posterior direction on transvaginal ultrasound examination . In eachSecondary outcome measures were bleeding duration, pain duration and level, unplanned surgical evacuation, blood transfusion, pelvic infection, uterine or cervical damage, and patient satisfaction. A combination of Interviewer-administered questionnaires and patients’ symptom check sheets were used to collect the demographic and clinical details. Patient satisfaction was assessed by questions included in the questionnaire. Participants were asked, “overall, how will you rate your experience with the treatment that you received?” responses on a two-point scale “I am satisfied” or “I am not satisfied.” The infection was diagnosed clinically and biochemically in suspected patients, and all adverse effects were managed as per ward protocol. Statistical data were analyzed using IBM SPSS Statistics, version 21.0 . One-way ANOVA or student’s t-test was used to analyze the differences in the continuous variables. The differences in proportions were analyzed by the chi-square test. A p-value of ≤0.05 was acknowledged to be statistically significant.Table The complete evacuation of the uterus was achieved in 95.2% (60/63) of patients in the MVA group and 70.3% (45/64) of patients in the expectant management group (Table Table The need for the second procedure for the uterine evacuation with DNC was less in the MVA group when compared to expectant management (Three vs. 19). The rate of blood transfusion and infection events did not differ statistically between the groups, although they were found to be less in the MVA group. There was no incidence of uterine perforation or cervical damage. Patient satisfaction was higher in the MVA method .This trial has compared the effectiveness and safety of MVA with expectant management in patients with first trimester pregnancy loss. Based on our study, it has been shown that MVA had a statistically significant success rate in achieving complete evacuation when compared to expectant management . It has been found that evacuation with MVA is more effective in the incomplete miscarriage type than in missed miscarriage (100% vs. 93.75%). In the past, the effectiveness of MVA was compared with electric vacuum aspiration (EVA) and traditional DNC, and the effectiveness of MVA in our study was comparable to the results of the previous studies -15,18,19Our trial has achieved complete evacuation in 70.3% (45/64) of patients in the expectant management arm. In contrast, the other studies’ overall success rate of expectant management varied from 44.2% to 94.4%, and this wide variation could be due to factors such as the type of miscarriage and duration of follow-up ,20,21. ASurgical procedures clear the retained products quicker than expectant management, where the uterus naturally contracts and evacuates its contents, possibly resulting in more prolonged bleeding. In our trial, the duration of vaginal bleeding experienced by the MVA group was smaller than the expectant management group . Similar results were found in the previous studies that compared surgery vs. expectant management; however, the surgical management of these studies was the traditional DNC ,21.In the present study, patients in the MVA group experienced pain for less duration compared with the expectant group . A study comparing surgical vs. expectant management done by Wael et al. showed a comparable, statistically significant, and higher number of days of pain  in both groups. However, the surgical management in that study was DNC . Pain isThe incomplete evacuation rate was less with MVA. In our study, only three (4.8%) from the MVA group and 19 (29.6%) patients from the expectant management group had incomplete evacuation and undergone surgical evacuation under general anesthesia. A study done by Milingos et al. on MVA showed a comparable rate of incomplete evacuation and required surgical evacuation (3.26%) . In our Only one (1.6%) patient from the MVA group and three (4.7%) patients from the expectant management group were treated for infection with antibiotics. No statistical difference was noted between the groups in this study related to pelvic infections. The rate of infections in the MVA group in the present study was in concordance with the results of other studies ,25. AlthMany studies that compared the MVA with other surgical managements have proven that MVA is a safe procedure for treating miscarriage and found that MVA was associated with no or minimal serious complications such as cervical damage or uterine perforation -15,22,24In evaluating patient satisfaction related to treatment modality, overall patient satisfaction was high with MVA compared to expectant management (93.7% vs. 65.3%). Other studies comparing MVA with EVA or with medical management found no significant differences in terms of patient satisfaction ,27. A stA cost-effective analysis was not included in this study. Based on the Annual Health Bulletin report of the Ministry of Health Sri Lanka 2015, 60% of the total gynecology-related hospital admissions were due to first trimester miscarriage. Among these, 78% of the patients underwent surgical management . In Sri LimitationsAn estimation of vaginal blood loss was not performed as there are difficulties accurately measuring the amount of blood loss practically due to subjective variations in the visual estimation.A cost-effective analysis could not be done due to practical difficulties.Our study has shown that MVA is an effective and safe method without significant complications and has a higher patient satisfaction rate. It can be done as an office procedure under local anesthesia and is considered a viable alternative to traditional surgical options for managing first trimester miscarriage after considering various factors, including patients’ preferences.


External evidence is commonly used to inform survival modeling for health technology assessment (HTA). While there are a range of methodological approaches that have been proposed, it is unclear which methods could be used and how they compare.This review aims to identify, describe, and categorize established methods to incorporate external evidence into survival extrapolation for HTA.Embase, MEDLINE, EconLit, and Web of Science databases were searched to identify published methodological studies, supplemented by hand searching and citation tracking.Eligible studies were required to present a novel extrapolation approach incorporating external evidence  within survival model estimation.Studies were classified according to how the external evidence was integrated as a part of model fitting. Information was extracted concerning the model-fitting process, key requirements, assumptions, software, application contexts, and presentation of comparisons with, or validation against, other methods.n = 5), piecewise (n = 7), and general population adjustment (n = 9), plus a variety of “other” (n = 8) approaches. Most methods were applied in cancer populations (n = 13). No studies compared or validated their method against another method that also incorporated external evidence.Across 18 methods identified from 22 studies, themes included use of informative prior(s)  were excluded from this review.Several methods were identified in this review, with common themes based on typical data sources and analytical approaches. Of note, no evidence was found comparing the identified methods to one another, and so an assessment of different methods would be a useful area for further research.This review aims to identify methods that have been used to incorporate external evidence into survival extrapolations, focusing on those that may be used to inform health technology assessment.We found a range of different approaches, including piecewise methods, Bayesian methods using informative priors, and general population adjustment methods, as well as a variety of “other” approaches.No studies attempted to compare the performance of alternative methods for incorporating external evidence with respect to the accuracy of survival predictions. Further research investigating this would be valuable. Appropriate estimation of OS over a lifetime horizon is critical to reliably estimate the total costs and outcomes associated with a given treatment strategy.Health technology assessment (HTA) makes use of clinical- and cost-effectiveness evidence for health care interventions to support policy decision making. While not an explicit requirement, contemporary HTA processes usually involve a submission made by the manufacturer of the intervention  under assessment, which often requires estimation of overall survival (OS) within a cost-effectiveness analysis for both the intervention (and its comparator[s]), particularly in the context of cancer therapies. However, trial-based extrapolations are subject to a number of limitations, usually related to sample size, data maturity , and trial design features, which may confound estimates of OS (such as crossover or subsequent therapy). Clinical trials are designed to evaluate the efficacy of a given intervention , whereas HTA is focused on its effectiveness . To address some of the limitations of trial-based survival estimation for HTA, methods that move away from being based solely on pivotal trial data warrant consideration—a sentiment echoed in a number of previously published studies.47Typically, estimates of OS for a new intervention and its comparator(s) are based on data collected from a pivotal clinical trial . conducted a review of methods used when extrapolating survival from randomized trials using external data . While this review provides a helpful description of methods that have been previously proposed in the literature to incorporate external data into survival extrapolations, the review was not systematic and a number of more recent studies have since been published. In addition, some methods may rely on external information, as opposed to external data, for example, integration of clinical expert opinion. The review by Jackson et al. was concerned only with studies that made use of external data, and so there may be other methods that were not discussed that adopt a broader view of external evidence.Jackson et al. Furthermore, we expand the scope of the review by Jackson et al. by considering methods that leverage external information sources. Following identification of such methods, we aim to describe and categorize each of the methods to provide an overview of current approaches to make use of external evidence within survival estimation and identify areas to focus future research efforts.The purpose of this review was to systematically identify methods for estimating OS that incorporate an element of external evidence  within the model-fitting process. To our knowledge, no comprehensive systematic review of such methods has been conducted, with the most recent nonsystematic review being that of Jackson et al. “Pearl growing” refers to a search strategy in which a number of known, relevant studies  can be used to construct a search strategy to then identify other studies. Then, based on newly identified studies, subsequent searches can be run with additional search terms. The CPG approach leverages a selection of pearls from which suitable databases and search terms can be determined. The review by Jackson et al. provides a collection of 11 pearls from which an initial search strategy was developed.Systematic reviews of methods-based studies may be considered more challenging than reviews of clinical or other non–methods-based studies for several reasons. These include the presence of inconsistent terminology  and a lack of validated search filters. In addition, methods reviews do not easily fit within a standard PICO  format, which can further complicate designs of traditional search strategies. Therefore, for this review, a comprehensive pearl-growing (CPG) searching approach was deemed suitable .Supplementary Material. Forward and backward citation tracking was also undertaken to complement the formal database searches, to identify any relevant studies that were cited in each of the identified studies as well as subsequent studies that referenced the study after it was published.Based on the electronic databases in which the pearls were indexed, MEDLINE, MEDLINE In-Process, EMBASE, Web of Science, and EconLit were searched. The first iteration of the search strategy was designed with assistance from both an experienced information specialist and systematic reviewer, with search terms centered around the key themes of “survival,” “sources,” “extrapolation,” and method-specific terminology , based on the key terms used in the initially identified pearl papers. Given the broad range of different terminologies, it was anticipated that a relatively large proportion of hits would be excluded . After the first iteration, the search terms were updated to capture any missing terms identified in new “pearls,” and the search was rerun as a second iteration. Both search strategies are provided within the  review .In addition to the formal database searching, materials presented at previous meetings of the Professional Society for Health Economics and Outcomes Research (ISPOR) were also considered, through keyword searching via its Presentations Database. Emergent research in the context of HTA methodology has previously been presented at ISPOR meetings, including one of the pearls identified in the Jackson et al.The main inclusion criterion for the review was that studies were required to be “primary” methodological studies, including reference to use of external evidence for the estimation of survival-based outcome(s). In the context of this review, “primary” refers to any study that presents a novel method concerning the use of external evidence in survival extrapolation. Some studies may present an application of, and/or minor alterations to, preexisting methods, neither of which were deemed primary methodological studies for this review. Reviews of methodological studies were included at interim stages because they may contain a novel method developed by the review authors as a result of the review and because such reviews may aid with the identification of other primary studies. However, reviews of methods were ultimately excluded within the presentation of findings, unless as part of the review a primary methodological study was included.In addition to being a primary methodological study, included studies were also required to make use of external evidence. Here, the term “evidence” is used in preference to “data” or “information” in order to distinguish between different types of evidence that could be used. “Evidence” is used throughout this review to describe both data and information sources that may be used, noting that individual studies may use the terms “data” or “information” when describing specific methods.Economic evaluations were excluded from consideration, as it was anticipated that the title and/or abstract for the vast majority of published economic evaluations would be unlikely to contain sufficient detail to determine whether or not external evidence had been used to inform the estimation of survival. We deemed it impractical to review records from every economic evaluation and therefore considered economic evaluations to be outside the scope of this review. By limiting our review to methodological studies, we anticipated that we would identify the majority of methods that have been developed to include external evidence within economic evaluations. Methods were also excluded if they did not incorporate external evidence within the estimation of the survival model itself but instead referred to external evidence for validation or contextual purposes.A data extraction template was developed to extract relevant information from the identified studies. Two stages of screening were applied with 2 independent reviews (A.B. and G.S.), with disagreements settled by discussion and with an additional reviewer (N.L.) if needed. Any further disagreements were settled by consensus view via discussion with the remaining members of the review team (M.S. and G.B.). No formal quality assessment of the identified studies was planned, since the purpose of the review was to identify all relevant published methods, regardless of the quality of the studies themselves.The data extraction template focused on 5 categories: summary information, method requirements, application, validation, and any further commentary. Summary information was extracted to understand key features of the methods . Method requirements were identified to acknowledge what evidence would be required to apply a given method, what key assumptions are made as part of the model-fitting process, and what software package(s) are required. Information regarding the application of the method to a case study was extracted to understand in which contexts the methods had been applied. Information reported on the validation of the methods was recorded to ascertain if the authors had attempted any form of validation of the approach in other settings or compared with other approaches. Finally, further commentary was extracted to document, in the authors’ words, the advantages and disadvantages of their approach.The protocol for this review was registered as a record with the PROSPERO international prospective register of systematic reviews (CRD42020202034).1130 From the 22 studies, 18 distinct methods were identified.For the first iteration, a total of 5,871 records were identified prior to de-duplication. After de-duplication and primary screening based on titles and abstracts, 130 records remained as eligible for secondary screening. As noted previously, a large number of records were expected to be excluded at primary screening owing to the search strategy needing to capture a broad range of terminology. After full-text screening, 113 records were excluded, which left 17 records suitable for data extraction. The second iteration (ran with an updated search strategy based on the findings from the first iteration) resulted in a further 4 records for data extraction. One additional record was identified from hand searching, giving a total of 22 studies for extraction.For the purpose of this review, we sought to categorize methods by common themes that indicated broadly how the external evidence was leveraged within the model-estimation process. However, the categories used are not mutually exclusive, as some methods incorporated multiple elements of approaches to integrate external evidence.Based on the information extracted from each of the identified method studies, 3 main themes were identified:1118Piecewise methods: These methods involved the use of external evidence to inform extrapolations only after a specified point in time.20Methods based on the use of informative prior(s): Several methods included specification of informative priors within a Bayesian framework as a means of using external evidence.1927General population adjustment methods: These methods incorporated information relating to general population survival as the source of external evidence.30In addition to these, a range of “other” methods was also identified, which included some other mechanism related to the use of external evidence and did not fit within a theme.Supplementary Material, a Sankey diagram illustrates similarities between the methods. The next subsections further describe the features of the identified methods by theme, highlighting individual methods of particular interest. Full details for all identified methods, including data requirements, assumptions, software availability, and whether a frequentist or Bayesian perspective is taken, are provided in the data extraction table . A final subsection is presented that summarizes some key findings across all of the methods identified.By restricting the influence of external evidence to affect only estimates beyond a specified cut point, the use of piecewise methods means the external evidence addresses uncertainty in longer-term estimation of survival. The piecewise aspect of these methods may be considered the simplest of the approaches identified to incorporate external evidence, owing to the transparency of how the external evidence is used and because some of these methods can be implemented without specialist software. Nevertheless, their simplicity may also be viewed as their most important limitation, as each piecewise approach makes several strong  assumptions about the pattern of survival in the relevant population .1113 However, Nelson et al. considered a different type of piecewise model that adopted age as a time-based metric for longer-term survival estimation, as opposed to time since study entry. This was the only study identified that used age instead of time as the basis from which to incorporate external evidence and has intuitive appeal to ensure lifetime extrapolations exhibit face validity. Pennington et al. developed a piecewise model that was capable of using only summary-level data concerning a future point estimate of survival at a specific timepoint (or “landmark”), which could be useful where only limited information is available from an external evidence source.Several examples of piecewise models were identified, in which the hazard of death was assumed to follow that of an external population from a given time point.Methods that involve specification of informative prior(s) allow expectations around survival based upon external evidence to be built into the survival model used for extrapolation. The impact of this approach on extrapolations depends both on the strength of the prior specified and the nature of the evidence being used to inform the prior . For example, constructing a model in which the prior distribution for a given parameter implies that its value is approximately 1, on average, may not influence a model greatly if the parameter was already estimated to be close to 1, whereas a prior that stipulates approximately 10% of patients are alive at 10 y might have a large impact depending on the estimated proportion without a prior. which makes use of several different external evidence sources. The other approaches identified allowed informative priors to influence survival extrapolations in a more limited way. For example, Che et al. specified informative priors in terms of when the external evidence begins to influence the survival extrapolation and how long it takes before survival is explained entirely by the external evidence. Soikkeli et al. specified a model in which informative priors were imposed on the shape parameter of a parametric survival model fitted to the primary data source, based on the shape parameter value estimated when fitting the same model to different (but related) external data.The most comprehensive of the methods identified under this theme is the multiparameter evidence synthesis approach by Guyot et al.,) to be executed efficiently. This may explain, at least in part, their seemingly limited uptake within the HTA field, along with the fact that these methods may be seen as more complicated than frequentist approaches. A further complication is that of transparency regarding how to execute the methods in broader contexts, as these methods require coding expertise to produce extrapolations. As an example, the study by Demiris and Sharples includes a link to find executable code, but it is no longer valid (which is unsurprising given that Web addresses are likely to change over the course of 15+ y). The need for coding expertise may further dissuade uptake of these methods, despite their advantages.These methods can be considered only in a Bayesian framework and so require the use of specialist Bayesian analysis software  are assumed to be certain (such that no uncertainty in life table estimates is factored into model fitting), which separates this source of external evidence from other sources. A relative survival approach is featured in several studies, in which disease-specific survival is estimated relative to a background mortality survival estimate. This approach has been applied within the context of a range of parametric modeling approaches, including standard parametric models, restricted cubic spline models, and mixture-cure models, fitted in both a frequentist and Bayesian framework.28 Each of these approaches considers a different relationship between the hazards for the population under consideration and those of the general population, although the authors of this study suggest that an “internal additive hazards” approach  exhibited the greatest face validity for all data sets they considered.Outside of a formal relative survival approach, a number of methods were identified in which general population hazards were considered additive, were assumed to eventually converge to those based on a parametric model fitted to the trial data alone, gradually influenced survival estimation according to a “rolling extrapolation” algorithm, or could be used as the basis from which to apply a hazard ratio (HR) to estimate lifetime survival for the population of interest.General population adjustment methods have a distinct advantage compared with methods that rely on other sources of external evidence in that they can be applied for any disease area (and that life tables are readily available for most countries). However, therein lies the fundamental limitation of these methods: adjustments can influence extrapolations based on comparability only to the general population and not the population of interest . Some of these approaches would therefore be expected to have a limited impact on extrapolations, particularly if applied within the context of populations that experience disease-specific mortality far in excess of other-cause mortality.The “other” methods were those that used external evidence in a way that did not fit into any of the previously described themes. Examples include the following:external evidence used to inform the estimation of a cure fraction within a mixture-cure model,models constrained to predict prespecified survival proportions at landmark time points, based on external information,30 andparametric models fitted to the primary data source but values “plugged in” for parameters of these models from models fitted to external evidence,17methods that based extrapolations on external information that informs expectations of how relative hazard rates  are likely to change over time.While these methods reflect a broad range of different types of approaches to use external evidence, each imposes specific assumptions and/or requires an explicit decision to be made for how the external evidence can affect survival extrapolation. presented an approach that may be considered an alternative application of the method presented by Soikkeli et al., except within a frequentist approach and making a stronger assumption that parameters taken from one model can be deemed “fixed” and then be applied to estimate other results based on the external evidence. Another example of assuming “fixed” external data was the informed mixture-cure model by Felizzi et al., which essentially allowed for the “cure fraction”  to be fixed at a particular value, based on external evidence.Most of these methods were implemented in a frequentist framework, and so the external evidence aspect of the model was treated as “fixed.” In fact, Hawe et al. . This method included specifying informative priors on an estimated HR from 6 y, but the value of 6 y was considered a “fixed” input to the model. In this sense, while Bayesian approaches may be criticized for introducing subjective prior information into model fitting, a similar criticism could be made of many of these assumption-based approaches.The only method identified in this category that was fitted in a Bayesian framework was the multiparameter evidence synthesis approach by Guyot et al.Most of the methods made use of external data from either another clinical trial, a type of observational study or registry, and/or life tables. Observational studies may provide useful data in a population similar to that of the trial of primary interest yet may suffer from similar limitations to the trial itself, such as small sample sizes and limited durations of follow-up. Registry databases may provide data for a larger number of patients with longer follow-up, but usually these data will reflect a broader patient population. These databases may also include only limited information on factors such as stage of disease, prior treatments, and specific mutations that may be important to consider for HTA, raising issues around the comparability of populations within different data sources.The methods typically assumed complete generalizability of the population of interest and the external population(s), although some adjusted external data to account for potential imbalances. Within the studies identified, examples were presented mostly reflecting populations with cancer, but some studies included populations with cardiovascular disease (which tended to include larger sample sizes).No study included an evaluation of a proposed method against another published approach that also made use of external evidence as a means of testing the proposed method, yet applications were presented in several studies to compare against “standard” parametric modeling methods. This review identified a broad range of different approaches, covering piecewise, informative prior(s), general population adjustment, and “other” approaches. An important finding from our review was that none of the identified studies attempted to evaluate their method against another published approach that also made use of external evidence in a different way. This highlights a broad concern with the use of nontrial evidence in survival extrapolation, that there are a substantial number of approaches that have been put forward in the literature but little in the way of guidance in selecting an appropriate method under a given set of circumstances.External evidence is increasingly used for survival extrapolation within contemporary HTA, particularly given that the National Institute for Health and Care Excellence (NICE) recently launched its Real-World Evidence Framework to aid in its ambition to “use real-world data to resolve gaps in knowledge and drive forward access to innovations for patients.”Supplementary Material). While frequentist approaches may be considered simpler to implement and require less specialized statistical analysis software, a benefit of a Bayesian approach is that it allows for the analyst to control the degree of influence the external evidence is permitted to have on model parameters. Furthermore, a Bayesian analysis more naturally allows the propagation of parameter and model uncertainty through the entire decision model. These are important considerations for HTA, as decision makers should ideally be able to understand the extent to which external evidence affects extrapolations as well as the uncertainty inherent within the analysis.The methods identified as part of this review could theoretically be categorized based on the approach taken to statistical analysis: Bayesian versus frequentist. However, this was not pursued, as it was noted that many of the approaches identified could feasibly be applied within either framework, with the exception of the informative prior(s) methods, which can be implemented only within a Bayesian framework. However, the data extraction table provides details on whether a Bayesian or frequentist perspective was taken .1130Owing to the specification of a broad search strategy, a large number of studies were excluded. Some of the excluded studies detailed methods that were adjacent to the topic of survival extrapolation but did not meet the review inclusion criteria. For example, a study by Lewis et al.34 “matched” data from a registry to pivotal trial data to align inclusion criteria, yet matching methods are more commonly used in HTA to reduce the risk of bias when comparing different study populations. As another example, Guyot et al. made use of HRs to capture an expected duration of treatment effect (one aspect of the multiparameter evidence synthesis), yet HRs are more often the target of inference within a (network) meta-analysis. Estimation of relative treatment effects and extrapolation of survival are intrinsically linked, but methods were included in this review only if they were capable of yielding extrapolations of OS (and not simply measures of relative effects).The scope of this review was limited to survival extrapolation methods, but there was a notable overlap in methods used for survival extrapolation and methods used to construct indirect treatment comparisons. For example, Fisher et al. cited only 3 economic evaluations that were known by the authors to contain an external data methods component3537 and contained methods that were already identified from other studies. Therefore, while the exclusion of these types of study is a limitation, it is unlikely that important methods have been missed. However, it would be valuable to investigate which methods are being used in contemporary cost-effectiveness analyses; for this, it is necessary to undertake a different type of review focusing on economic evaluations and then determine from a full-text review which appear to use external evidence and which do not . A separate, standalone review of the contemporary use of external evidence to inform NICE appraisals of cancer drugs has also been undertaken by the study authors.Several limitations are acknowledged within the context of this systematic review. First, novel methods that are used only within the context of a de novo economic evaluation were excluded, given that (as previously mentioned) in order to comprehensively identify such methods, one would effectively need to screen all published economic evaluations to determine whether or not external evidence was used. It was therefore not practical to include economic evaluations within this review, which means that it is possible that relevant methods may have been missed. Reassuringly, Jackson et al.17 and full presentations can be accessed online. There may be methods presented at other meetings that were not identified by our review, but we suspected most conference proceedings would lack the detail required to fully describe a method and that novel methods presented at a conference would likely result in a subsequent paper, and therefore, we do not expect to have missed important methods.There is no standard terminology to describe external evidence, and authors used different terminology based on the specific sources cited. Some sources  may be referenced by name instead of “registry” and so may not have been identified by the search strategy if insufficient detail was otherwise provided in the title or abstract. However, it is likely that disease-specific registries would be referred to in methods papers as a case study and thus described accordingly as a registry within the abstract. In addition, we only considered conference presentations from the ISPOR database, selected as 2 studies were originally presented at an ISPOR meeting before journal publication,3941 As with the use of methods in the context of economic evaluations, another area for planned future research is a formal evaluation of methods under both real-life circumstances  and controlled circumstances , including how each method can reflect the inherent uncertainty associated with extrapolations.The performance of specific methods was not explicitly evaluated as part of this review, as it is expected that the performance of some methods may be affected greatly by the context in which it has been applied. For example, an age-based piecewise extrapolation method may perform better in an older versus a younger population, because background mortality is likely to have greater influence on survival extrapolations in an older group for whom life expectancy is shorter. Nevertheless, the strengths and weaknesses of each approach (as stated by the study authors) were extracted and summarized in a narrative synthesis, and the extent of evaluation performed by the study authors was assessed . Previous studies have assessed a range of extrapolation approaches in cancer populations, although none have included all of the methods described in this review.This review reports a summary of possible approaches to incorporate external evidence into survival extrapolations, on the basis of a systematic search of the literature. Several methods were identified with common themes that emerged, namely, methods that adopt a piecewise approach to introduce external evidence beyond a given time point, methods that incorporate external evidence through the specification of informative priors in a Bayesian framework, and methods that introduce general population data to adjust extrapolations. In addition, a number of “other” methods were also identified that rely on some other mechanism to integrate external evidence into model fitting.An important finding from this review was that no evidence was found comparing the identified methods to one another. This poses a challenge for all parties involved in HTA decision making, ranging from analysts needing to choose and defend a particular approach, to decision makers needing to base their decisions on reliable evidence using appropriate statistical methodology. As such, an assessment of different methods to incorporate external evidence would be a useful area for further research.On the basis of this review, we recommend that when researchers wish to leverage external evidence for survival extrapolation, they should carefully justify the approach taken to incorporate the evidence and why alternative approaches were not used. This should include details on how the external evidence was identified and the rationale for why the selected source of evidence was chosen . The method used and the analyses applied should also be clearly described, so that reviewers, decision makers, and other stakeholders can understand what external evidence has been used, how it influences estimations, and by how much. At present, it is not possible to make recommendations on the preferred methods for including external evidence to inform extrapolations, but the ultimate objective is to utilize methods that use appropriate evidence in a justifiable way to produce credible extrapolations.Click here for additional data file.Supplemental material, sj-docx-1-mdm-10.1177_0272989X231168618 for A Systematic Review of Methods to Incorporate External Evidence into Trial-Based Survival Extrapolations for Health Technology Assessment by Ash Bullement, Matthew D. Stevenson, Gianluca Baio, Gemma E. Shields and Nicholas R. Latimer in Medical Decision Making