Cervical screening programs use testing for human papillomavirus (HPV) genotypes. Different HPV types differ greatly in prevalence and oncogenicity. We estimated the impact of cervical screening and follow-up for each HPV type.For each type of HPV, we calculated the number of women needed to screen (NNS) and number of women needing follow-up (NNF) to detect or prevent one cervical cancer case, using the following individual level input data (i) screening and cancer data for all women aged 25 to 80 years, resident in Sweden during 2004 to 2011 ; (ii) HPV type-specific prevalences and screening histories among women with cervical cancer in Sweden in 2002 to 2011; (iii) HPV 16/18/other HPV prevalences in the population-based HPV screening program ; and (iv) exact HPV genotyping in a population-based cohort . Historical screening attendance was associated with a 72% reduction of cervical cancer incidence caused by HPV16  ) and a 54% reduction of cancer caused by HPV18 . One case of HPV16-caused cervical cancer could be prevented for every 5,527 women attending screening . Prevention of one case of HPV16-caused cervical cancer required follow-up of 147 HPV16–positive women . The NNS and NNF were up to 40 to 500 times higher for HPV types commonly screened for with lower oncogenic potential . For women below 30 years of age, NNS and NNF for HPV16 were 4,747 and 289, respectively, but >220,000 and >16,000 for HPV35,39,51,56,59,66,68. All estimates were either age-standarized or age-stratified. The primary limitation of our study is that NNS is dependent on the HPV prevalence that can differ between populations and over time. However, it can readily be recalculated in other settings and monitored when HPV type-specific prevalence changes. Other limitations include that in some age groups, there was little data and extrapolations had to be made. Finally, there were very few cervical cancer cases associated with certain HPV types in young age group.In this study, we observed that the impact of cervical cancer screening varies depending on the HPV type screened for. Estimating and monitoring the impact of screening by HPV type can facilitate the design of effective and efficient HPV-based cervical screening programs.NCT00479375, NCT01511328.ClinicalTrials.gov with numbers  Joakim Dillner and colleagues estimate the impact of cervical screening and follow-up for preventing and detecting one case of cervical cancer caused by each HPV type. Cervical screening programs now use testing for human papillomavirus (HPV).Different HPV types differ greatly in prevalence and oncogenicity, therefore screening for and further management of certain HPV types may cause excessive false positives and resource consumption.How cervical screening program may be impacted by screening for different HPV types has not been sufficiently studied.We integrated the Swedish nationwide data of HPV genotype and cervical screening history among cervical cancer cases as well as the general population and calculated “number needed to screen” and “number needing follow-up” for preventing and detecting one case of cervical cancer caused by each HPV type.The impact of cervical screening was very different from different HPV types: prevention or detection of one cervical cancer case caused by HPV16 involved much fewer women in screening and required much fewer being followed up, as compared to types with lower oncogenic potential, such as HPV35, 39, 51, 56, 59, 66, 68.In young women, screening and follow-up of HPV35, 39, 51, 56, 59, 66, 68 would require unreasonably large efforts per prevented or detected case, whereas in older women, screening and follow-up of these HPV types appeared reasonable.HPV18-related cervical cancer was inadequately prevented in cytology-based screening.Cervical screening programs may consider selecting which HPV types to screen for or follow-up, depending on women’s age.HPV vaccination is changing the HPV type-specific prevalence in the population, thus monitoring the impact of screening by HPV type can facilitate the design of effective and efficient HPV-based cervical screening programs.The major limitation is that HPV prevalences are changing over time, necessitating updated calculations of the impact. Elimination of cervical cancer as a public health problem is a globally prioritized goal issued by the World Health Organization (WHO). To achieve this goal, screening efforts that use an optimal screening test and management algorithms are needed. Following results from randomized clinical trials that demonstrated a greater cancer-protective effect when screening using human papillomavirus (HPV) testing as compared to cytology , HPV-basCervical cancer is caused by infection with oncogenic HPV types, of which the International Agency for Research on Cancer (IARC) recognizes 12 HPV types as oncogenic  and 1 HPV type as “probably oncogenic” (HPV68) ). For HPV59, the corresponding numbers were 1 case per every 1,339,680 women in screening  and follow-up of 4,389 HPV59–positive women to prevent one case . For HPV51, NNS and NNF could not be estimated, because too few HPV51–positive cervical cancer cases were detected during 10 years in the country of Sweden .The impact numbers by HPV types varied by age. Among women aged below 30 years, the NNS and NNF to prevent one cervical cancer case by HPV16 was about 50 to 60 times lower as compared to the low oncogenicity group of viruses , whereas among women aged between 51 and 60 years, the NNS and NNF to prevent one cervical cancer case by HPV16 was only about 10 to 20 times lower compared to the low oncogenicity group of viruses .We found that the 12 oncogenic HPV types with additional 2 probably/limited oncogenic types that are included in commonly used HPV testing platforms have widely varying impact numbers, both for the number needed to screen and the number needing follow-up.The impact numbers, based on and in addition to the existing knowledging of HPV type-specific prevalence and oncogenicity, provide more integrated and explicit information in order to calculate (i) the number of tests needed for benefit; and (ii) the number of follow-up visits needed for benefit. Screening visits and gynecological follow-up visits demand resources and may involve adverse effects and it is therefore desirable to design screening programs with as high impact as possible.Today, there are many HPV screening platforms that include extended HPV genotyping. If the NNS for a particular HPV type is high, meaning that the impact of the type to the screening program is low, the program may consider evaluating whether that type needs to be included in the screening. Similarly, the NNF data could be used to design referral strategies. Options could be, e.g., to directly refer women with HPV types with low NNF to gynecological examination, but require repeat testing or other triaging before referring women positive for HPV types with high NNF.The impact numbers other than HPV16, especially the intermediate and lower oncogenicity types, tended to vary greatly by age. Among older women, these impact numbers were low with narrow CIs, whereas among younger women these impact numbers tended to be high with very wide CIs. These wide CI were due to very few cases with those types among young women to be detected, and very few cases with those types in the upcoming 10 years to be prevented. The small number of cases itself suggests a low importance of these types in this age group. This suggests that strategies where only selected types are screened for or followed-up may be appropriate in younger age groups. In particular, consideration of no screening or no follow-up in women under 30 years of age may be warranted for the lower oncogenic types HPV35, 39, 51,56, 59, 66, and 68. Screening is always an ethical balance between the benefit and the adverse effects , shouA major limitation of the study was using several assumptions to integrate data over different calendar periods and ages, which was described and discussed in the Methods section. Another limitation in our calculation of impact number is, in younger age groups, that certain HPV types, particularly HPV51, had very few or even no cases, which hindered the estimation for NNS and NNF for cancer prevention. Nevertheless, since these types caused very few cases regardless of screening history, they are potentially negligible types to screen for. A further limitation is, regarding the cervical cancer cases being negative for oncogenic HPVs in tumor blocks, we know little about their HPV infection status and types in the years before cervical cancer diagnosis, thus we cannot predict how HPV-based screening would impact this group. We will be able to know more in the near future with accumulated data from HPV-based screening. Nonetheless, since few cervical cancer cases in young women were negative for oncogenic HPVs in tumor blocks, our estimates for young women were barely affected by this issue.To conclude, the 12 oncogenic HPV types and 2 commonly tested probably oncogenic types have large variations in their impact numbers, and thus different cervical cancer screening efficiency. Use of HPV screening tests that focus on HPV types with low number needed to screen and referral algorithms focusing on HPV types with low number needing follow-up may be considered, especially for younger women. To increase screening effectiveness, strategies to follow-up HPV18 positivity may need to be improved. Impact numbers can be monitored over time, following the change of HPV type-specific prevalence and screening effectiveness, to timely provide data to the screening program for consideration of possible adjustment.S1 STROBE Checklist(DOCX)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S1 Protocol(PDF)Click here for additional data file.S2 Protocol(PDF)Click here for additional data file. 6 Apr 2023Dear Dr Dillner, Thank you for submitting your manuscript entitled "HUMAN PAPILLOMAVIRUS TYPE-SPECIFIC IMPACT NUMBERS IN CERVICAL SCREENING" for consideration by PLOS Medicine.Your manuscript has now been evaluated by the PLOS Medicine editorial staff and I am writing to let you know that we would like to send your submission out for external peer review.However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. 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For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it. Please ensure that the paper adheres to the PLOS Data Availability Policy  make it clearer from the beginning that data sources are not all for the whole population and b) say what the age range is that defines ‘all women’?Materials and methods, p5: ‘by screening history’ – this seems to be applying an assumption, rather than being based on women’s actual screening history. Is this correct? If so, can it be more explicit? On p4, it says that each woman’s screening history was retrieved – so how were these data used? It would actually be very helpful to have a table that lists the actual data sources and says how these data are then used.Tables, figures: Age groups should be reported consistently. E.g. Fig 1, first box, Swedish women aged 23-84; left had side box has 25-84; middle boxes – there are numbers stratified by different age groups – please explain in legend. Table 1 start at <30 – is this from age 23 or 25? And >=65, is this up to 84 or all over that age? Table 4, why are preventable cases 61-80 included in age group 51-60? If oldest age group is 84 elsewhere, why not here?Discussion: use of the term ‘impact numbers’ needs to be revised because it’s confusing. E.g. para 2, lines 3-4, ‘A program could e.g. decide to use a screening test that does not test for HPV types with high impact numbers’ I think it means if the numbers NNS and NNF are high – but it sounds like the opposite, that the HPV type wouldn’t be included if the impact of testing for it were high.Discussion, p8, para 3: ‘This suggests that strategies where only selected types are screened for or followed-up may be particularly appropriate in younger age groups.’ It would be good to see a bit about the ethical aspects and public communication of deciding not to screen for an oncogenic HPV type that is included in a test and for which a result would be available, even if the number needed to screen is high.Requests from the editors:GENERAL COMMENTSPlease respond to all editor and reviewer comments.Please include page numbers and line numbers in the manuscript file. 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Please see our author guidelines for more information: The summary should include 2-3 single sentence, individual bullet points under each of the questions.https://journals.plos.org/plosmedicine/It may be helpful to review currently published articles for examples which can be found on our website here INTRODUCTIONp.3: Please define WHO in the Introduction.p.3: Please define HPV in the Introduction.p.3: Please define IARC in the Introduction.Please address past research and explain the need for and potential importance of your study. Indicate whether your study is novel and how you determined that. If there has been a systematic review of the evidence related to your study (or you have conducted one), please refer to and reference that review and indicate whether it supports the need for your study. 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If a reported analysis was performed based on an interesting but unanticipated pattern in the data, please be clear that the analysis was data-driven.PLOS Medicine requests that main results are quantified with 95% CIs as well as p values. Please include. When reporting p values please report as p<0.001 and where higher as the exact p value p=0.002, for example. For the purposes of transparent data reporting, if not including the aforementioned please clearly state the reasons why not.Please include any important dependent variables that are adjusted for in the analyses.Suggest reporting statistical information as detailed above – see under ABSTRACTp.4: Please change “This study was based on entire population of women live in Sweden from 1990s to 2019, […]” to “This study was based on the entire population of women living in Sweden from the 1990s to 2019, […]”. Please check your manuscript carefully for grammar, spelling and punctuation.p.4: “We integrated these data sources through cross-linkage at the individual level using personal identification number, and generate fundamental parameters of […]” – please change “generate” to “generated” and ensure to keep the tense consistent throughout the manuscript.p.4: Please define PCR in the Methods.p.4: Please write “Table 1”/“Figure 1” instead of “table 1”/”figure 1” and check throughout your manuscript.p.7: Please change “pseudo scenario” to “pseudo-scenario” and check carefully throughout your manuscript to keep a consistent spelling.p.7: Please remove the comma in “Figure 4 compares the prevalence and risk profile across 14 HPV types in the pseudo scenario of no screening, in a two-dimensional graph”.p.7: Please change “Y-axis displays the age-standardized prevalence in percentage of each type in the population, and x-axis displays the incidence of cervical cancer among women positive for each HPV type in absence of screening.” to “The y-axis displays the age-standardized prevalence in percentage of each type in the population, and the x-axis displays the incidence of cervical cancer among women positive for each HPV type in absence of screening.”.p.7: Please re-write the sentence starting with “Screening likely to have contributed to around […]”. Editorial suggestion: Screening likely contributed to approximately 72% (69%-74%) reduction in cases caused by HPV16 and by types other than 16 and 18, whereas it contributed to only 54% (41%-63%) reduction in cases caused by HPV18 (Table 2).p.7: “The impact numbers for cervical screening in the population, i.e NNS and NNF to detect orprevent one case of cervical cancer, […]” – please change “i.e” to “i.e.”.p.7: Please check the grammar and punctuation for the following sentence: “For HPV51 NNS and NNF could not be estimated because too few HPV51-positive cervical cancer cases were detected during 10 years in the country of Sweden) .”Please present numerators and denominators for percentages, at least in the Tables [not necessarily each time they're mentioned].DISCUSSIONPlease present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.Please remove all subheadings within your Discussion e.g., limitations and other considerations.p.8: “In particular, the lower oncogenic types HPV35, 39, 51, 56, 59, 66, 68 may be considered not screen for or not directly refer to follow-up in women below age 30.” – please change to “In particular, the lower oncogenic types HPV35, 39, 51,56, 59, 66, 68 may not be considered for screening or direct follow-up in women under 30 years of age.”.p.8: Please define CIN2+ and CIN3+ in the Discussion.p.9: The third paragraph  seems redundant as it repeats the statements of the previous paragraphs. Please be careful to make key statements and avoid repetition.p.9: “Nevertheless, as these types caused very few cases regardless of screening historyimply that they are potentially negligible types to screen for.” – please change to “Nevertheless, since these types caused very few cases, regardless of screening history, they imply that they are potentially negligible types to screen for.”.FIGUREShttp://journals.plos.org/plosmedicine/s/figures.For all Figures, please ensure that you have complied with our figures requirements Please provide titles and legends for all figures (including those in Supporting Information files).Please define abbreviations used in the table/figure legend of each figure and/or table (including those in Supporting Information files).In Figure 2, please provide 95% CIs.Figure 3: Please define the scale on the y-axis as “%” is not sufficient in this case.Figure 4: The description of the different scales used in Figure 4  should not be in brackets in the title, but part of the figure description.Please consider avoiding the use of red and green in order to make your figure more accessible to those with colour blindness.Please indicate in the figure caption the meaning of the whiskers in Figure 5 and 6.REFERENCEShttp://www.ncbi.nlm.nih.gov/nlmcatalog/journals), and are appropriately formatted and capitalised.Please ensure that journal name abbreviations match those found in the National Center for Biotechnology Information (NCBI) databases , oncogenicity and screening effectiveness were collected from different groups and over more than 20 years. By incorporating these data in the analyses, the authors have calculated the number need to screen (NNS) and the number need to follow-up (NNF) to detect or to prevent a case of cervical cancer by each HPV type. These impact numbers were substantially different among the 14 HPV types evaluated (12 high-risk and 2 probably/possibly oncogenic). On the basis of the results, the authors provide a stratification of these HPV types , and indicate  the most effective screening strategy, that can imply no screening or no follow up for infections by the lower oncogenic types, especially among the youngest age groups. The approach allows recalculation of the impact numbers over time, and this is an important aspect. The cervical cancer screening is being implemented in many countries with high-riskHPV testing as primary test; moreover, the use of a risk-based approach to manage the women with a positive screening result (where HPV genotyping could play a role as triage test) and the integration of primary (anti-HPV vaccination) and secondary (screening) preventive measures need to implement the protocols and monitor the effectiveness of the screening. The authors claim that these results could apply to other countries with similar type-specific HPV prevalences and similar screening efficiency; generalizability will probably be limited by differences in the prevalence of different HPV types  and by the substantial differences in anti-HPV vaccination coverages. Anyhow, the topic of this paper is of great importance in the field of cervical cancer prevention, where instruments to device the best strategies to adapt and personalize the screening strategies is highly needed. Moreover, it is important to the health community at large because these changes to be effective need that all the healthcare professionals give updated and concordant informations to the women. MINOR OBSERVATION:-TABLE 1: a footnote reporting the distribution of the HPV types in the three subgroups could be usefully addedReviewer #2: The paper represtnts a clever use of existing data. It will change our way to think about genotyping in cervical cancer screening.I have only few comments to improve the roprting and a comment on the interpretation that could be a matter for discussioon. AbstractI do not understand why NNS and NNF are reported only for women below 30, while for the all ages is reported only the variation without any absolute number. For the reader is not easy to follow the results as reported in the abstract. I think it should be clear that protection estimates come from screening with Pap test, not HPV test. Instead of the generic disclaim "Although reasonable limits for impact numbers may differ between settings" a more specific comment on the different level of protection given by HPV now could be appropriate. IntroductionClear and well written. I only suggest better explaining how the number need to detect and number need to prevent interacts: the two desirable effect of screening, i.e. early detection of cancers and prevention of cancers, are additive and there is no way that any positive event is counted twice. I have a comment about the type specific NNS. It can be high for two reasons, low prevalence in the population or low oncogenic risk. If the issue is low prevalence, the type specific NNS to screening is not relevant for the decision making of including it or not, since the real NNS is that for all types. The NNS of the overall screening test is not the average of the NNS of single HPV types. As a paradox if we use a taxonomy that splits the HPV 16 in different variants, also the NNS of each HPV 16 variant will increase dramatically, without changing nothing about the efficiency or effectiveness of the test. MethodsAccording to my understanding of the computations made by the authors, the underlying model is simple but robust; its simplicity is a strength because it is also transparent. Nevertheless, simplicity of the model implies many assumptions. I suggest to add a paragraph or a box reporting all the implicit assumptions made by your model. The main issues are two, from first glimpse of the described methods: 1) the model assumes a steady state, i.e. the analysis of HPV types in screened and unscreened population assumes that these proportion are the product of a stable dynamic between infections and progression to cancers in the two populations (this assumption is acceptable but should be explicit); probably you are also assuming that incubation time is equal for all types. The fact that this assumption is not true is probably the explanation for a different ratio between HPV16 and HPV low oncogenic NNS and NNF across ages: the incubation time is different, so there are few cancers from low-oncogenic types in younger women.2) how do you treat the large part of cancers that are not positive for any HPV oncogenic type? According to table 1 and 2, it seems that they are distributed in the proportions of 16, 18 and other oncogenic but maybe I am wrong. It would be better to make an explicit statement on this point. I do not understand why all the measures are "age standardized". Actually all the relevant parameters are age-specific and all the counterfactual scenarios are estimated on a "standard" population, I do not see the need for standardizing. Particularly for type-specific HPV prevalence, standardization may be relevant only for the comparison of the screened and non-screened population that have different age structures. If this is the rationale, I suggest to explain it. All the other parameters are always age specific.ResultsFirst line of the results and figure 2 reports incidence in 2004-2011, while table two reports cancers from 2002 to 2011. Can you clarify?Please define the time of incidence is per 100,000/y or cumulative for the 8-year period? Table 2. Could you report also the protection of screening for HPV-negative cancers? Figure 2. y-axis report if the incidence is annual or cumulative.Discussion pag 8 second paragraph, I do not agree with the sentence: "An alternative strategy to use the NNS data could e.g. be to decide that detection of HPV types with high impact numbers is a normal screening result". As discussed before, if we adopt a different taxonomy and we give a different name to all HPV16 variants, the NNS will increase for each of these, the same for HPV 45 in some populations where it is extremely rare, but it will be always worth to include it among the oncogenic ones. Furthermore, low prevalence of a HPV type increases the type specific NNS but not the burden of assessment tests. NNS is relevant to decide if we have to screen or not at all, but it is not relevant for deciding which type should be included in the set of HPV types to test. pag 9, second paragraph: when mentioning the limitation that the screening effectiveness assessment was conducted for cytology-based screening, I think it is worth to report how much is expected to improve the protection with HPV based test, particularly for adenocarcinoma; an estimate could be given based on the pooled analysis of European trials (reference n 1) .Reviewer #3: Alex McConnachie, Statistical ReviewThis review considers the statistical elements of the paper by Wang et al, looking at impact numbers in cervical screening in Sweden, in relation to HPV type and age.The paper is a very nice analysis of routinely collected data, and data collected as part of other studies, and an excellent demonstration of how this can be used to inform public health policy. The impact numbers and how they are calculated are explained in great detail. The use of bootstrapping to generate confidence intervals is appropriate. The presentation is, on the whole, very clear.I have one or two comments, which are minor, bordering on the trivial.The date range for the study population is a little vague; should exact dates be given?The paragraph giving descriptions of the NNS and NNF to detect or prevent one case is very good, in that it accurately describes each parameter. However, it is quite dense. Could some consideration be given to presenting these as formulas? Would some readers find that easier to follow?In Table 2, do the columns headed "Population" add anything? Could it be made clearer that the columns headed "Screened in last 10 years" actually relate to the hypothetical situation where everyone is screened (and similarly for the "Unscreened in last 10 years")? It is clear from the footnotes, but could perhaps be clearer in the headers.In Table 4, the columns are labelled as "Number needed to screen to detect (or to prevent) one case". However, only the top half of the table reports NNS, and the bottom half gives NNF. Maybe the columns should simply say "To detect one case" and "To prevent one case".In Figure 2, the abbreviation "ASR" is not defined.In Figures 5 and 6, the confidence intervals are asymmetrical, and those to the left of each panel are quite compressed. Would the figures work better with the x-axes on a log scale? Each figure has a different range on the x-axis - would showing on a log scale allow these to have a common scale? Would that be slightly better?Reviewer #4: The current revision of the paper includes an interpretation in the abstract that is non-committal. Focusing on the NSN and NNF for women over 30 years might be more useful for an interpretation to put money toward screening and following up the abnormals. Methods - it is inappropriate to classify HPV types by whether or not they are in the Merck based nonovalent vaccine- do not let industry drive your definitions, let the science. Why don't you group the HPV types in the way that BD has grouped them according to aggressiveness of oncogenesis with 16/18/31 as separate highest risk types, and then 33/58 together, then 52 and 45 separately as medium high risk, then type 51 alone as a lower risk HR type, then 35/39/68 grouped together, and 56/59/55 grouped together. At least this grouping of HPV types is associated with risk of CIN 3+ over time. What is your assumption about HPV vaccination? You are using the Swedish population and creating pseudo scenarios that are dependent on the current HPV vaccination type and uptake remaining constant. Is this true? How does this limit your conclusions?Your definition of NNS and NNT are too simplistic. You are creating an ideal situation where you only value screening for follow up if a cancer is detected. Screening is always a BALANCE between over-screening and leaving cancers on the table. You might check with a Bayseian mathetmatician about the pseudo scenarios you have created that the level of error inherent in each.Figur2-What percentage of the population did not have a screen prior to her diagnosis? Why was she diagnosed with cervical cancer? symptoms? incidental for something else? what is the age distribution of these cancers? Figure 4 is not offering any information other than a plot. Age stratification needs to be above 30, not above 50 - or you need to provide adequate justification for not using 30 and older for your analysis. Discussion section needs to state that the limitation of racial/ethnicity diversity in Sweden means these data cannot be extrapolated to other continents where the population homogeneity is dissimilar. HPV 18 discussion is interesting - was the screening cytology based? if we went to HPV primary testing would we have missed those cancers? if we went with HPV 18 testing followed by Dual Stain, would those cancers have been missed in screening? Is it a fault of the screening that these cancers were not detected, or was it a fault of the women not coming in for screening?Any attachments provided with reviews can be seen via the following link:[LINK] 5 Jul 2023AttachmentResponse_to_Editors_reviewers_20230630.docxSubmitted filename: Click here for additional data file. 4 Sep 2023Dear Dr. Dillner,Thank you very much for re-submitting your manuscript "Impact of different types of Human Papillomavirus in cervical screening: Population-based estimations" (PMEDICINE-D-23-00933R2) for review by PLOS Medicine.I have discussed the paper with my colleagues and the academic editor and it was also seen again by two reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:[LINK]***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.Please also check the guidelines for revised papers at plosmedicine@plos.org) if you have any questions or concerns.We expect to receive your revised manuscript within 1 week. Please email us , which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. 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Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.plosmedicine@plos.org.Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.If you have any questions in the meantime, please contact me or the journal staff on We look forward to receiving the revised manuscript by Sep 11 2023 11:59PM.   Sincerely,Alexandra Schaefer, PhDAsscoiate Editor PLOS Medicineplosmedicine.org------------------------------------------------------------Requests from Editors:GENERALThank you for considered and detailed responses to editor and reviewer comments.Please see below for further minor points that we request you respond to in full.Please add 'years’ to ages stated throughout your manuscript.We note that the Supporting Information file S2  provides important details for the understanding of the paper. We leave it to your discretion whether you wish to include it in the main paper.Thank you for providing a copy of your study protocol (S7) as a supporting information file. Please send this in the original language and an English translation. Please detail any deviations from this study protocol in the Methods section of your manuscript.ACADEMIC EDITOR COMMENTSThank you for the opportunity to read the revised manuscript. The authors have made extensive changes and the description is much clearer. I apologise for the rather impolite comment about the writing in the previous version. The authors had addressed my main comments.1. Introduction: line 83, “Impact numbers [12] are a suitable measurement.” Whilst these are described in the next para, it would help to at least introduce ‘population’ and ‘disease’ impact numbers because they are not widely used terms.2. Line 144: spelling, ”assumPtions”3. Line 155: wording, suggest “We found two publications suggesting…”4. Line 177: “HPV vaccination has yet noticeably affected the study population…” should it be “…has NOT yet…”?5. Fig 1: I cannot see where footnote c refers to6. Lines 370-1: “NNS will therefore be constantly monitored…to timely adjust screening strategies.” This implies that a decision to choose which HPV types should be followed up has already been made. However, in response to Reviewer #2’s comment about HPV type-specific prevalence, the authors say, “Which conclusion to make is up to the program – we are simply providing data that can be considered.” Can the authors clarify whether this strategy has already been adopted?7. Line 411: wording “…to timely inform the screening program for adjustment.” As above, this sentence needs to be clarified – and made grammatically correct.EDITORIAL COMMENTSWhen revising your manuscript, please consider that your manuscript needs to be accessible to a wide audience and aim to improve your writing for this purpose.COMPETING INTERESTYou indicated that authors KS has received research grants from Merck and Co, LLC. For authors with ties to industry, please indicate whether any of the interests has a financial stake in the results of the current study.DATA AVAILABILITY STATEMENTThank you for agreeing to make your data available. At this time, please provide the link to the data repository and accession numbers required for access.TITLESince the title must be nondeclarative, we suggest changing your title to “Outcomes of cervical screening by human papillomavirus genotype: a population-based study in Sweden” or similar. We suggest changing the short title to “HPV type-specific outcomes in cervical screening” or similar.ABSTRACTl.18 suggest: “Cervical screening programs use testing for human papillomavirus (HPV) genotypes.”l.32: Please change ‘can’ to ‘could’.In the last sentence of the Abstract Methods and Findings section, please describe the mainlimitation(s) of the study's methodology. The statement “However, it can readily be recalculated in other settings and monitored when HPV-type specific prevalences change.” should be included in the discussion .Please revise your Abstract Conclusion. The statement that you found different screening impacts for different HPV types is very vague. Also, findings observed in your study should be presented in past tense. We suggest, “In this study, we observed that the impact of cervical cancer screening varies depending on the HPV type screened for. Estimating and monitoring the impact of screening by HPV type can facilitate the design of effective and efficient HPV-based cervical screening programs.” or similar.AUTHOR SUMMARYYour author summary requires revision. The summary should include 2-3 single sentence, individual bullet points under each of the questions (Why Was This Study Done? What Did the Researchers Do and Find? What Do These Findings Mean?). Please note that the text should be distinct from the scientific abstract. In the final bullet point of ‘What Do These Findings Mean?’, please describe the main limitations of the study in non-technical language.https://journals.plos.org/plosmedicine/It may be helpful to review currently published articles for examples which can be found on our website here INTRODUCTIONl.62: Please define ‘HPV’ at first use (you first define ‘HPV’ in l.64).l.77: Please change ‘suggest’ to ‘suggests’.l.102: Please exchange ‘hope’ with ‘aim’.METHODS AND RESULTSPlease ensure that, when possible, the 95% confidence intervals quantified for the main results are reported in the main text. For description of age, please add ‘years’ (e.g. l.133 ‘women aged 23-29’). Please revise throughout the entire manuscript.I.121 onwards: would benefit from being split into shorter paragraphs to improve reader accessibility.l.122: Please change to “women in the capital region of Stockholm”.l.144: Please change ‘assumtions’ to ‘assumptions’.l.155: Please change to “We found two publications suggesting […]”.l.163: Please change the format of ‘4254’ to ‘4,254’. Please ensure consistency in number format and revise throughout the entire manuscript (e.g. l.166 ‘2850’ or l.206 ‘1000’).l.177-179: Please clarify whether HPV vaccination has or has not yet affected the study population. Editorial suggestion: “HPV vaccination has not yet had a noticeable impact on the study population included in this study: data were not available from birth cohorts of women vaccinated in the school-based or similar high-coverage HPV vaccination program.”l.184: We note that you usually write the word “other” in quotation marks (here: other 12 types). Please revise and ensure to use a consistent format throughout the entire manuscript.l.211-212: Please note that the citation does not meet the requirement of PLOS reference formatting. Please remove ‘Heller et. al'.I.252: This statement should be presented early in the method section. Please move to perhaps follow the subheading at line 105.I.274: It might be helpful to re-define the population size such that ‘30%’ can be quantified.l.279: Please change ‘S2 Figure’ to ‘Figure S2’.l.286: Please add a comma following ‘and 33’. ll.283-287: Please note that results should be described in past tense. I.302/305: Suggest ‘lower’ instead of ‘reduced’.DISCUSSIONl.337: Please change ‘has’ to ‘have’.l.341: Please change ‘does test’ to ‘tests’.l.386: Please change ‘Data from European HPV-based screening trial’ to ‘Data from a European HPV-based screening trial’.l.391: Please change ‘limitation of study’ to ‘limitation of the study’.l.392: Please change ‘method’ to ‘methods’.l.404: ‘Possibly/probably’, please use one or the other of the two words but not both.FIGURESPlease consider avoiding the use of red and green in order to make your figure more accessible to those with colour blindness.Figure 1: Please cite the reference numbers in square brackets as done in the main text. Citations should be preceding punctuation.Figure 1: Please check the footnotes. The figure does not contain footnote ‘c’, but contains an asterisk which is not defined. Please define ‘HPV’, ‘FFPE’. For description of age, please add the unit ‘years’. Figure 2: Please add a unit for ‘age’.Figure 3: Please add a unit for ‘age’. Please define ‘HPV’.Figure 4: Please define ‘HPV’. Please clearly define the meaning of the dots and lines for the reader. Perhaps, ‘Impact numbers (dots) and 95% confidence intervals (lines)…’ in the title?Figure 5: Please add a unit for ‘age’. Please define ‘HPV’. Please add a reference for the definition of the oncogenic types (as done in Table 1). Please clearly define the meaning of the dots and lines for the reader. Perhaps, ‘Impact numbers (dots) and 95% confidence intervals (lines)…’ in the title?TABLESTable 1: Please add a unit for ‘age’. Please define ‘HPV’. Please cite the reference numbers in square brackets.Table 2: Please revise the number format . Please change ‘pseudo scenario’ to ‘pseudo-scenario’. Please add a unit for ‘age’. Please define ‘HPV’. In the footnote ‘e’, please write ‘age-standardized’ with a capital ‘A’. Where is footnote ‘b’ in the table?Table 2: The definition of footnote ‘f’ might be misleading. We suggest: “Difference between the estimated number of cases in pseudo-scenario that all women were unscreened in last 10 years and the estimated number of cases in pseudo-scenario that all women were screened in last 10 years”.Table 2: In footnote ‘g’, please introduce ‘CI’ as the abbreviation for ‘confidence intervals’.Table 3: For clarity, we suggest exchanging the asterisk (*) and the slash (/) with ‘multiplied by’ and ‘divided by’. Please revise the number format . Please define ‘HPV’. Please add a unit for ‘age’. Please define ‘+∞’. Table 4: Please revise the number format . Please define ‘HPV’. Please add a unit for ‘age’. Please add a reference for the definition of the oncogenic types (as done in Table 1).SUPPLEMENTARY MATERIALS1 Appendix: Please add a unit for ‘age’. Please define ‘HPV’ at first use. Please replace the word ‘cited’ with ‘Accessed’. Is the 1st ref a web ref? If so, please include the access date.S3 Table: Please define ‘CL’ and the meaning of ‘+∞’. Please revise the number format . S3 Table A: Please add a definition for ‘all ages’. Could the CIs be presented in one column and separated by a comma? S3 Table B: Please add a unit for ‘age’. Please add a reference for the definition of the oncogenic types (as done in Table 1).REFERENCEShttp://www.ncbi.nlm.nih.gov/nlmcatalog/journals) and are appropriately formatted and capitalised.Please revise reference 33 regarding the abbreviated journal title. Please ensure that journal name abbreviations match those found in the National Center for Biotechnology Information (NCBI) databases  that would be appropriate to tag, including your own, your coauthors’, your institution, funder, or lab. Please respond to this email with any handles you wish to be included when we tweet this paper.Comments from Reviewers:Reviewer #1: The authors have adequately responded to my comment, and I have no additional observations.Reviewer #2: The authors improved the manuscript that is much clearer now.There is still an issue that I cannot agree and that should be discussed at least: the interpretation of the type-specific NNS. The authors answered to my comment #4 as follows: "When designing a screening program, it is essential to know if the condition screened for is rare or common. Which conclusion to make is up to the program - we are simply providing data that can be considered." I do not think this sentence applies to single genotypes. In fact, we start from HPV16 that is the most common and the most oncogenic type, then the decision, for the first level test of screening, is if we want to screen for HPV16 alone or HPV16 + the second most oncogenic type (let's say HPV18), therefore the condition HPV16+HPV18 will be more common than HPV16 alone, and so on. Single genotypes with high NNS will never be rare as condition to be screened, because they will be always considered as add on to a pool of other genotypes. Therefore, the NNF will determine if they have enough risk to be included in an efficient screening. NNS may give an idea of the public health impact of including a genotype or not, but cannot help to make the most efficient selection of types. In the discussion, I suggest to revise the sentence "If the NNS for a particular HPV type is high, meaning that the impact of the type to the screening program is low, consideration could be given as to whether screening could be discontinued for that type" (lines 318-320). This is surely true for a high NNF, but for a NNS the considerations are different: a high NNS may give a low value if we have to choice between a commercial test including that type and another not including it, but this is a different situation from deciding to dismiss screening for a single type. Reviewer #3: Alex McConnachie, Statistical ReviewThe authors have addressed all of my (minor) comments, and I have nothing else to add.Any attachments provided with reviews can be seen via the following link:[LINK] 20 Sep 2023AttachmentRespondsToComments_JW20230912.docxSubmitted filename: Click here for additional data file. 2 Oct 2023Dear Dr Dillner, On behalf of my colleagues and the Academic Editor, Nicola Low, I am pleased to inform you that we have agreed to publish your manuscript "Impact of cervical screening by Human Papillomavirus genotype: Population-based estimations" (PMEDICINE-D-23-00933R3) in PLOS Medicine.aschaefer@plos.org. Thank you for your thoughtful and detailed responses to the editorial comments. We are pleased that the next step will be to publish your manuscript, but there are some minor stylistic and presentation aspects that should be addressed prior to publication. We will carefully check that these changes have been made. If there are any questions concerning these final requests, please do not hesitate to contact me at Please see below for further minor points that we request you respond to:1) Academic Editor comment: The text of footnote c in Figure 1 doesn't match what is in the box – it is difficult to match up the populations of women screened  in the box with the legend, which talks about women in Stockholm 2012-2016. A reader cannot follow the numbers easily.2) Abstract: Please change ll.38-39 to: “The primary limitation of our study is that the NNS is dependent on the HPV prevalence that can differ between populations and over time.3) l.414: Please provide a reference for “largely related to HPV18”.4) References: Please exchange ‘cited’ with ‘accessed’ when stating when websites were accessed (reference 15).5) Figure 3: Please adjust the colors of the figure legend according to the colors used in the figure and explain in the figure description that the shaded areas represent the 95% confidence intervals.Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. 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