PEER REVIEW HISTORY ARTICLE DETAILS TITLE (PROVISIONAL)

Transcription

1 PEER REVIEW HISTORY BMJ Open publishes all reviews undertaken for accepted manuscripts. Reviewers are asked to complete a checklist review form ( and are provided with free text boxes to elaborate on their assessment. These free text comments are reproduced below. TITLE (PROVISIONAL) AUTHORS REVIEWER REVIEW RETURNED GENERAL COMMENTS ARTICLE DETAILS Effectiveness of 23-valent Pneumococcal Polysaccharide Vaccine on Elderly Long-Term Cancer Survivors: A Population-based Propensity Score Matched Cohort Study Chiou, Wen-Yen; Lee, Moon-Sing; Hung, Shih-Kai; Lin, Hon-Yi; Lo, Yuan Chen; Hsu, Feng-Chun; Tsai, Shiang-Jiun; Li, Chung-Yi VERSION 1 REVIEW Robert Menzies University of New South Wales Australia 21-Nov-2017 This seems to be a well-controlled observational study on an issue that continues to be debated internationally - the effectiveness of PPV23 against pneumonia, as opposed to invasive pneumococcal disease. My main concerns are around clarifying to what extent this study relates to non-invasive pneumonia, and adding clear statements that it does not relate to immunocompromised people and is limited to 2 years post-vaccination. The title should include 'Matched', as in a 'matched cohort study'. Methods Regarding the matching process, this implies that some controls and perhaps cases were excluded as they were not or could not be matched to a corresponding case or control. These exclusions are not mentioned in Figure 1 or the text. More detail is needed on diagnosis of bacterial pneumonia hospitalisations. In particular, is the aetiology of pneumonia hospitalisations usually known, or do most cases have unknown aetiology? Is aetiology usually diagnosed from a blood culture, in which case they will be invasive cases, and the effectiveness of PPV23 against these cases is well accepted, or is sputum culture commonly used or is lobar pneumonia diagnosed from x-ray, which is likely to include non-invasive cases, the subject of controversy regarding the vaccine's effectiveness? Regarding the exclusion of people who died before 2009, was this done for vaccinated and unvaccinated people? as the flowchart implies this was only done for the unvaccinated, if so a potential source of bias. Also regarding deaths, an estimate of effectiveness against all-cause death should be conducted, as bias could be introduced when censoring people at death, if death due to 1

2 REVIEWER REVIEW RETURNED GENERAL COMMENTS conditions other than pneumonia is associated with vaccination. The authors claim that information contained in the dataset is regarded as complete and accurate, as false diagnostic reports lead to severe penalties. What about inaccurate or incomplete records on vaccination status? Have these been assessed and found to be as complete and accurate? Conclusions I do not agree with statements in the abstract, discussion and conclusions that this study provides evidence to support the ACIP recommendation related to vaccination of the those suffering immunosuppression related to cancer. This study is in long-term cancer survivors who are no longer on immunosuppressive therapy. The authors cite a high incidence rate in this population, but there are many potential reasons for differences between rates in different countries. The authors should stress that this study follows a cohort through only two years post-vaccination, which has repeatedly been associated with the period of highest vaccine effectiveness. Statements that confounding has been 'avoided' (abstract and discussion) or 'prevented' (discussion) should be tempered to something like 'reduced', as it is not possible to be certain that measures taken in a cohort study will totally eliminate confounding. Study limitations sections should not include strengths (all cancer treatment modalities were included... all cancer types...). And surely a limitation of the study is that it is observational, not randomised, and is limited to routinely-collected data, ie. does not include relevant data that are not routinely collected. Discussion p.17, please use an alternative term to 'normal' people, eg. 'who had not (received chemotherapy)'. What is a registry for beneficiaries? There are several mentions of the term 'incidence density', which should be 'incidence' or 'incidence rate'. Maya Leventer-Roberts Clalit Research Institute, Tel Aviv, Israel Icahn School of Medicine at Mount Sinai, New York, New York 12-Dec-2017 This is an interesting approach on a challenging topics, that chooses an important subpopulation and uses standard measurements. However, there are a few major limitations: 1) The age limit of 75 is greater than the more common worldwide recommendation of 65, and raises a question as to whether these findings are truly applicable beyond this specific context. Noting the rates of disease in the general population aged (and among those who self-pay for the vaccine) would be of great interest. Additionally, does a <50% vaccination rate despite free access suggest alternative explanations for the self-selection? This should be addressed. 2) The confounder of influenza vaccination is not adequately addressed given the significant differences between the cohort and matched controls. It is quite possible that it alone explains the effect, particularly given that hopsiatlized pneumonia is the most common 2

3 complication. It is not clear from the paper which confounders were included in the final adjusted model and what their contributions were. Does table 5 demonstrate adjustment for all these variables in a single model or a bivariate analysis for each individually? If it is the former, it appears to be far too many confounder variables for such a small sample size. If it is the later, it doesn't address the need to address influenza vaccination as a confounder by indication. 3) The written English is not acceptable. I would recommend a thorough editorial review. VERSION 1 AUTHOR RESPONSE Reviewer(s)' Comments to Author: Reviewer: 1 Reviewer Name: Robert Menzies University of New South Wales, Australia Comments of reviewer 1: This seems to be a well-controlled observational study on an issue that continues to be debated internationally - the effectiveness of PPV23 against pneumonia, as opposed to invasive pneumococcal disease. My main concerns are around clarifying to what extent this study relates to non-invasive pneumonia, and adding clear statements that it does not relate to immunocompromised people and is limited to 2 years post-vaccination. We revise our conclusions of both abstract and main manuscript, as below: The benefit of PPSV23 vaccination in long-term cancer survivors lasts at least two years. (On revised manuscript, conclusion section, page 23, and on revised Abstract, conclusion paragraph, page 5) We add below descriptions into Materials and Methods section, Measurements of Endpoints and Potential Confounders subsection of main manuscript: All-cause pneumonia in this study included both invasive pneumonia and non-invasive pneumonia and excluded viral pneumonia, pneumonia due to bacteria other than Streptococcus pneumoniae, and influenza. Clinically, patients with a pneumonia patch or positive sputum culture would be diagnosed as having pneumonia and receive treatment. In the database of our study, less than 5% of the allcause pneumonia cases were invasive. The pneumonia in most of our hospitalized patients was noninvasive, and this finding was the subject of previous controversy regarding the vaccine's effectiveness. (On revised manuscript, Materials and Methods section, Measurements of Endpoints and Potential Confounders subsection, page 11, 3rd paragraph and page 12, 1st paragraph) The title should include 'Matched', as in a 'matched cohort study'. We changed our manuscript title to A Matched Population-based Cohort Study Suggest A Reduced Risk of Pneumonia Hospitalization in Old Long-term Cancer Survivors with 23-valent Pneumococcal Polysaccharide Vaccination according to your suggestion. (On revised manuscript, Title, page 1) 3

4 Methods Regarding the matching process, this implies that some controls and perhaps cases were excluded as they were not or could not be matched to a corresponding case or control. These exclusions are not mentioned in Figure 1 or the text. We add below descriptions into Materials and Methods section of main manuscript: Considering the relatively low vaccination rate, self-selection for vaccination may exist. To reduce the bias of confounding by indication that people with a history of frequent pneumonia would have a greater tendency to receive vaccination than the general population, we propensity-score-matched each vaccinated patient to two unvaccinated patients. The propensity score was calculated from the age on January 1, 2009, gender, and number of pneumonia hospitalizations over the previous three years. Unmatched patients or controls were excluded. Exactly 377 vaccinated patients and 754 unvaccinated patients were finally recruited (Figure 1). (On revised manuscript, Materials and Methods section, Patients and The Study Groups subsection, page 11, 2nd paragraph) We also revise Figure 1 itself and add below figure 1 legend: ## To reduce confounding by indication, propensity score matching was used. Non-matched cases or controls were excluded. (On revised Figure 1 and Figure 1 legend) More detail is needed on diagnosis of bacterial pneumonia hospitalisations. In particular, is the aetiology of pneumonia hospitalisations usually known, or do most cases have unknown aetiology? Is aetiology usually diagnosed from a blood culture, in which case they will be invasive cases, and the effectiveness of PPV23 against these cases is well accepted, or is sputum culture commonly used or is lobar pneumonia diagnosed from x-ray, which is likely to include non-invasive cases, the subject of controversy regarding the vaccine's effectiveness? We add below descriptions into Materials and Methods section, Measurements of Endpoints and Potential Confounders subsection of main manuscript: All-cause pneumonia in this study included both invasive pneumonia and non-invasive pneumonia and excluded viral pneumonia, pneumonia due to bacteria other than Streptococcus pneumoniae, and influenza. Clinically, patients with a pneumonia patch or positive sputum culture would be diagnosed as having pneumonia and receive treatment. In the database of our study, less than 5% of the allcause pneumonia cases were invasive. The pneumonia in most of our hospitalized patients was noninvasive, and this finding was the subject of previous controversy regarding the vaccine's effectiveness. (On revised manuscript, Materials and Methods section, Measurements of Endpoints and Potential Confounders subsection, page 11, 3rd paragraph and page 12, 1st paragraph) Regarding the exclusion of people who died before 2009, was this done for vaccinated and unvaccinated people? as the flowchart implies this was only done for the unvaccinated, if so a potential source of bias. In the original Figure 1, the 120 vaccinated patients excluded because they received vaccination outside the defined period 2008/10~2008/12, included 11 vaccinated patients who died before year 4

5 2009 and received vaccination outside the defined vaccination period. Because we already defined the vaccination period 2008/10~2008/12 and patients who died before 2009 were all excluded, we did not emphasize in the original figure 1 that vaccinated people who died before 2009 were also excluded. Actually, all unvaccinated and vaccinated people survived at least until the end of the defined vaccination period, January 1, To prevent misunderstanding, we revise Figure 1 flowchart and add below figure 1 legend to clarify flowchart: # The vaccination period is set to reduce the bias of competing risk of death, i.e., by excluding people who did not receive vaccination because they died too early to receive vaccination. All cases and controls survived at least until the end of the defined vaccination period, January 1, (On revised Figure 1 flowchart and Figure 1 legend) We also add below descriptions into Materials and Methods section, Patients and The Study Groups subsection of main manuscript: We defined the vaccination period as October 2008 to December 2008, to reduce bias associated with the competing risk of death, i.e., people dying too early to receive the vaccination. All patients and controls survived to the end of the vaccination period, i.e., January 1, 2009, at least. Therefore, we excluded 556 patients and controls who died before 2009 and 109 patients who received PPSV23 outside this vaccination period (Figure 1). The follow-up period for both the vaccinated and unvaccinated groups started on January 1, 2009 and ended on the date of withdrawal from the NHI program, death, or study termination (December 31, 2010). (On revised manuscript, Materials and Methods section, Patients And The Study Groups subsection, page 10, 3rd paragraph and page 11, 1st paragraph) Also regarding deaths, an estimate of effectiveness against all-cause death should be conducted, as bias could be introduced when censoring people at death, if death due to conditions other than pneumonia is associated with vaccination. About estimate of effectiveness against all-cause death, we add a new Supplement Figure (efigure 2) and efigure 2 showed no significant different for overall survival times between vaccinated and unvaccinated people. We add efigure 2 result into Results section of both main manuscript and abstract, as below: The cumulative pneumonia incidence was significantly lower in PPSV23-vaccinated than unvaccinated patients (efigure 1, P = 0.028) and overall survival time was similar between the two groups (efigure 2, P = 0.136). (On revised manuscript, Results section, page 17, 1st paragraph, and on revised Abstract, page 5, 2nd paragraph, and on new efigure 2 legend) Except overall survival time in efigure 2, we also add another new Supplement Figure (efigure 1), cumulative pneumonia incidence of patients with and without PPSV23, into our revision. In the Materials and Methods section, Statistical analysis subsection of manuscript, we add below descriptions: The Kaplan-Meier method was used to estimate cumulative incidence of pneumonia hospitalization and overall survival time. (On revised manuscript, Materials and Methods section, Statistical analysis subsection, page 14, 1st paragraph) 5

6 Besides, to reduce bias that different observation time among patients, i.e. patients died early due to any cause and had no or less chance to have a pneumonia, a person-years approach was used to determine incidence rate. We add below descriptions into Materials and Methods section, Statistical analysis subsection: The incidence rate of pneumonia hospitalization was calculated as the ratio of the number of pneumonia hospitalizations to the number of person-years of follow-up, to reduce bias that different observation time among patients, i.e. patients died early due to any cause and had no or less chance to have a pneumonia. (On revised manuscript, Materials and Methods section, Statistical analysis subsection, page 13, 3rd paragraph) Besides, patients with age over 75 years old, very close to life expectancy in Taiwan, is a very old population, so death is an important issue need to be considered. In this study, a person-years approach was used to determine incidence rate, reducing bias due to time of observation differences between vaccinated and unvaccinated groups. Therefore, we add below descriptions into Discussion section, Study strengths subsection: Third, a person-years approach was used to determine incidence rate, reducing bias due to difference in observation time between the vaccinated and unvaccinated groups, which is important because of the relatively short life expectancy of elderly long-term cancer survivors. (As in the Discussion section, Study strengths subsection, page 22, 2nd paragraph) Also, as mentioned above, we defined a period of vaccination to reduce bias associated with competing risk of death, and add below descriptions into the Materials and Methods section, Patients and the study groups subsection of manuscript: We defined the vaccination period as October 2008 to December 2008, to reduce bias associated with the competing risk of death, i.e., people dying too early to receive the vaccination. All patients and controls survived to the end of the vaccination period, i.e., January 1, 2009, at least. (As in the Materials and Methods section, Patients and the study groups subsection, page 10, 3rd paragraph) The authors claim that information contained in the dataset is regarded as complete and accurate, as false diagnostic reports lead to severe penalties. What about inaccurate or incomplete records on vaccination status? Have these been assessed and found to be as complete and accurate? The PPSV23 vaccine code used in this study is a drug code rather than diagnosis code. The coding of drug code is considered more accurate and complete than diagnosis code, because drug code of vaccination is related to payment of vaccine by government in our health insurance system. Not like diagnosis code, drug code is coding only at the day when people receive vaccination. If doctor forgot to make a vaccine drug code but patient actually received vaccination, then hospital or clinics would not get payment. If doctor used vaccine drug code but patients actually did not receive vaccination, then doctor would be considered a thief of this health insurance system and would be prosecuted and fined hundred times money of vaccine payment. We add below description into Materials and Methods section, Sources of Database subsection of main manuscript: The PPSV23 vaccine code used in this study is a drug code rather than diagnosis code. 6

7 (On revised manuscript, Materials and Methods section, Sources of Data subsection, page 9, 2nd paragraph) Conclusions I do not agree with statements in the abstract, discussion and conclusions that this study provides evidence to support the ACIP recommendation related to vaccination of the those suffering immunosuppression related to cancer. This study is in long-term cancer survivors who are no longer on immunosuppressive therapy. The authors cite a high incidence rate in this population, but there are many potential reasons for differences between rates in different countries. Most long-term cancer survivors, like prostate cancer, breast cancer, are indeed not in the immunosuppressive status. Only some long-term cancer survivors with chronic comorbid conditions such as liver and renal dysfunction caused by previous cancer treatments, such as liver cancer patients received repeat radiotherapy to liver, would have a risk of long-term neutropenia. We delete sentences added evidences to support ACIP's recommendation in conclusion section of both abstract and main manuscript. (Deleted on revised manuscript, Discussion section, page 22, and Conclusion section of main manuscript, page 23, and abstract, page 5) We add below description into Introduction section of main manuscript to further clarify: In some long-term cancer survivors with chronic comorbid liver and renal dysfunction caused by previous cancer treatments, such as repeat radiotherapy to the liver, there is the added risk of longterm neutropenia. (On revised manuscript, Introduction section, page 8, 2nd paragraph) The authors should stress that this study follows a cohort through only two years post-vaccination, which has repeatedly been associated with the period of highest vaccine effectiveness. We add below description as the third limitation of this study, into Limitation subsection: Third, this study follows a cohort post-vaccination for only two years, which is the period repeatedly associated with highest vaccine effectiveness. (On revised manuscript, Discussion section, Limitation subsection, page 23, 2nd paragraph and on Strengths and limitations of this study, page 6, Point 4) We also revise conclusions of both main manuscript and abstract to clarify, as below: Conclusion: The benefit of PPSV23 vaccination in long-term cancer survivors lasts at least two years. (On revised manuscript, Conclusion section, page 23, and on revised Abstract, page 5) Statements that confounding has been 'avoided' (abstract and discussion) or 'prevented' (discussion) should be tempered to something like 'reduced', as it is not possible to be certain that measures taken in a cohort study will totally eliminate confounding. We change the below term avoid in manuscript to reduce : 7

8 Fourth, this study adjusted several confounding factors (including influenza vaccination, vaccination period, anti-cancer treatments, co-morbidities, and personal socioeconomic status), reducing confounding by indication that vaccinated people may be more aware of the need for protection against pneumonia than unvaccinated people. (On revised manuscript, page 6, Strengths and limitations of this study, Point 3, and on Discussion section, Study strengths subsection, page23, 1st paragraph) We also change below term prevent in manuscript to reduce : Second, this study used propensity score matching to select unvaccinated patients, which reduced confounding by indication. Third, a person-years approach was used to determine incidence rate, reducing bias due to difference in observation time between the vaccinated and unvaccinated groups, which is important because of the relatively short life expectancy of elderly long-term cancer survivors. (On revised manuscript, Discussion section, Study Strengths subsection, page 22, 2nd paragraph) This study used a propensity score matching strategy to select unvaccinated patients, which reduced confounding by indication. (On revised manuscript, page 6, Strengths and limitations of this study, Point 1) A person-years approach was used to determine incidence rate, reducing bias due to time of observation differences between vaccinated and unvaccinated groups, which is important because of the relatively short life expectancy of elderly long-term cancer survivors. (On revised manuscript, page 6, Strengths and limitations of this study, Point 2) Study limitations sections should not include strengths (all cancer treatment modalities were included... all cancer types...). And surely a limitation of the study is that it is observational, not randomised, and is limited to routinely-collected data, ie. does not include relevant data that are not routinely collected. Thanks for your suggestions. We delete the sentence all cancer treatment modalities were included and the sentence... included all cancer types in Discussion section, Limitation subsection. (On revised manuscript, Discussion section, Limitation subsection, page 23, 2nd paragraph) We add below descriptions as the second limitation in Limitation subsection: Second, it is observational, not randomized, and is limited to routinely collected data, i.e., does not include relevant data that are not routinely collected. (On revised manuscript, Discussion section, Limitation subsection, page 23, 2nd paragraph) Discussion p.17, please use an alternative term to 'normal' people, eg. 'who had not (received chemotherapy)'. We change the term normal people to control patients who had not : In a single-institution study in Norway, PPSV23 vaccination elicited adequately protective pneumococcal IgG antibody levels without significant difference, except for serotype 4 in both 35 cancer patients who had just received chemotherapy and 38 control patients who had not. 8

9 (On revised manuscript, Discussion section, page 18, 1st paragraph) What is a registry for beneficiaries? A registry for beneficiaries is a sub-database of NIRHD database, which record data about socioeconomic variables, like urbanization level, geographic region, and monthly income-based insurance premium. We add below description into Materials and Methods section: The database contained ambulatory care claims, inpatient hospitalization claims, a registry of beneficiaries which recorded socioeconomic data, and a registry of catastrophic illness. (On revised manuscript, Materials and Methods section, Sources of Data subsection, page 10, 1st paragraph) There are several mentions of the term 'incidence density', which should be 'incidence' or 'incidence rate'. We change all incidence density term in our manuscript to incidence rate, as your suggestion. (On revised Abstract, page 5, Results section, and on manuscript, page 13, Materials and Methods section, Statistical Analysis subsection, and on revised Table 3 and 4 title) Reviewer: 2 Reviewer Name: Maya Leventer-Roberts Clalit Research Institute, Tel Aviv, Israel Icahn School of Medicine at Mount Sinai, New York, New York Comments of reviewer 2: This is an interesting approach on a challenging topics, that chooses an important subpopulation and uses standard measurements. However, there are a few major limitations: 1) The age limit of 75 is greater than the more common worldwide recommendation of 65, and raises a question as to whether these findings are truly applicable beyond this specific context. Noting the rates of disease in the general population aged (and among those who self-pay for the vaccine) would be of great interest. Additionally, does a <50% vaccination rate despite free access suggest alternative explanations for the self-selection? This should be addressed. We add below limitation description into Discussion Section, Limitation subsection of main manuscript: Fourth, because the free vaccine policy applies only to those over age 75 years old, the conclusion of this population-based cohort study applies to this age group rather than the more common age over 65 group. (On revised manuscript, Discussion section, Limitation subsection, page 23, 2nd paragraph, and on page 6, Strengths and limitations of this study, Point 5) 9

10 We add below description into Materials and Methods section of main manuscript: Considering the relatively low vaccination rate, self-selection for vaccination may exist. To reduce the bias of confounding by indication that people with a history of frequent pneumonia would have a greater tendency to receive vaccination than the general population, we propensity-score-matched each vaccinated patient to two unvaccinated patients. The propensity score was calculated from the age on January 1, 2009, gender, and number of pneumonia hospitalizations over the previous three years. Unmatched patients or controls were excluded. Exactly 377 vaccinated patients and 754 unvaccinated patients were finally recruited (Figure 1). (On revised manuscript, Materials and Methods section, Patients and The Study Groups subsection, page 11, 2nd paragraph) We also add below description into Materials and Methods section of main manuscript: To reduce confounding by indication, as people with higher health awareness would be more likely to be vaccinated than the general population, we also adjusted for several socioeconomic variables, including urbanization level, geographic region, and the monthly income-based insurance premium. (On revised manuscript, Materials and Methods section, Measurements of endpoints and potential confounders subsection, page 13, 2nd paragraph) 2) The confounder of influenza vaccination is not adequately addressed given the significant differences between the cohort and matched controls. It is quite possible that it alone explains the effect, particularly given that hopsiatlized pneumonia is the most common complication. It is not clear from the paper which confounders were included in the final adjusted model and what their contributions were. Does table 5 demonstrate adjustment for all these variables in a single model or a bivariate analysis for each individually? If it is the former, it appears to be far too many confounder variables for such a small sample size. If it is the later, it doesn't address the need to address influenza vaccination as a confounder by indication. Table 5 was results of univariate and multivariate analysis with all covariates included. We perform other two multivariate analysis, with only significant covariates in the univariate model included, and with/without influenza vaccination status included (influenza vaccination status was not significant in the univariate analysis model). We put these two other multivariate analysis results into a new supplement etable 3. (etable 3: Multivariate analysis with significant covariates in univariate model included only and with/without influenza vaccination status) We add below description about etable 3 results into Results section of main manuscript: The results of multivariate analysis including significant covariates in the univariate model (etable 3) were almost the same as the above results (Table 5). PPSV23 was a significant factor in both table 5 and etable 3, with airr = (all covariates included, P = 0.030), (only univariate significant variates and influenza vaccination status adjusted, P =0.029), and (only univariate significant variates adjusted, P =0.030), respectively. All covariates that were significant in Table 5 remained significant in etable 3 and the nonsignificance of influenza vaccination status in Table 5 remained so in etable 3 (etable 3, airr = 1.065, P = 0.748). (On revised manuscript, Results section, page 17, 2nd paragraph) We add below description into Materials and Methods section of main manuscript: 10

11 Since the incidence rate followed a Poisson distribution, we used a multivariate log-linear Poisson regression model to calculate the incidence rate ratios (IRRs) with all covariates included. We also performed multivariate analyses with only significant covariates in the univariate model included, and with/without influenza vaccination status included (influenza vaccination status was not significant in the univariate analysis model), and these results was listed in the supplement data. (On revised manuscript, Materials and Methods section, Statistical analysis subsection, page 13, 3rd paragraph, and page 14, 1st paragraph) We also revise Table 5 title to clarify: Table 5. Crude and adjusted incidence rate ratio (IRR) of pneumonia hospitalization in association with PPSV23 vaccination in univariate and multivariate analysis (all covariates included). (On revised Table 5 title) About the confounder of influenza vaccination, we revise below descriptions in Results section of main manuscript: In both univariate and multivariate analysis, all covariates adjusted, influenza vaccination had no significant effect on pneumonia hospitalization (IRR = 1.060, P = 0.755; airr = 1.030, P = 0.883; Table 5). (On revised manuscript, Results section, page 16, 2nd paragraph) All covariates that were significant in Table 5 remained significant in etable 3 and the nonsignificance of influenza vaccination status in Table 5 remained so in etable 3 (etable 3, airr = 1.065, P = 0.748). (On revised manuscript, Results section, page 17, 3rd paragraph) 3) The written English is not acceptable. I would recommend a thorough editorial review. After we finished revision, we invited a medical editor who is a native English speaker associated with MedCom Asia, Inc., to edit English writing of our manuscript in 2018/1. This manuscript was then sent back to us on January 24, The English editor who edited our manuscript has been a professional editor and writer for several years and is a member of American Medical Writers Association. We also upload the certification that the English editor has edited our manuscript. REVIEWER REVIEW RETURNED GENERAL COMMENTS VERSION 2 REVIEW Maya Leventer-Roberts Clalit Research Institute 20-Feb-2018 This was a major revision to a number of fundamental concerns to the design of the study. The revisions clarified and address the concerns. VERSION 2 AUTHOR RESPONSE -Authors must include a statement in the Methods section of the manuscript under the sub-heading 'Patient and Public Involvement'. If patients and or public were not involved please state this. 11

12 Dear editor, We add the below statements into our Methods section under the sub-heading 'Patient and Public Involvement': Patient and Public Involvement This is a database study using NHIRD. No patients or public were involved in setting out the research question or developing the outcome measures, nor were they involved in developing plans for design or implementation of the study. No patients or public were asked to advise on interpretation or writing up of results, nor was the burden of the interventions on patients assessed. The results of the research were not disseminated to those study patients. (On revised manuscript, Methods section, page 10, Patient and Public Involvement subsection) Reviewer(s)' Comments to Author: Editorial Requests: - Please revise your title to indicate the research question, study design, and setting. This is the preferred format for the journal. See published articles for examples. Please note that we do not accept manuscripts with declarative titles (which is currently the case with your manuscript) Dear editor, We change our manuscript title from A Matched Population-based Cohort Study Suggest A Reduced Risk of Pneumonia Hospitalization in Old Long-term Cancer Survivors with 23-valent Pneumococcal Polysaccharide Vaccination to Effectiveness of 23-valent Pneumococcal Polysaccharide Vaccine on Elderly Long-Term Cancer Survivors: A Population-based Propensity Score Matched Cohort Study according to your suggestion. (On revised manuscript, Title, page 1) - Please work to improve the quality of the English throughout your manuscript. We recommend asking a native English-speaking colleague to assist you. Please focus some effort on the quality of the abstract. Dear editor: We improve the English quality of our manuscript, especially abstract. (On revised manuscript, Abstract, page 4 and 5) Besides, on our previous revision process, we has invited a medical editor who is a native English speaker associated with MedCom Asia, Inc., to edit English writing of our manuscript. The English editor who edited our manuscript has been a professional editor and writer for several years and is a member of American Medical Writers Association. We also upload the certification that the English editor has edited our manuscript. - Please revise the abstract so that the conclusions follow more logically. As there is nothing in the abstract to indicate that you are only looking at a two year period, the conclusions currently don't logically follow. Dear editor: We add the sentence After two years of follow-up into our results section in abstract. We also changed our conclusion from The benefit of PPSV23 vaccination in long-term cancer survivors lasts at least two years. to PPSV23 vaccination was associated with a significantly reduced rate of pneumonia hospitalization in long-term cancer survivors. (On revised manuscript, Abstract, page 5, Results and Conclusions sections; On revised manuscript, Conclusion section, page 23) Reviewer: 2 Reviewer Name: Maya Leventer-Roberts Institution and Country: Clalit Research Institute 12

13 Comments for the authors below: This was a major revision to a number of fundamental concerns to the design of the study. The revisions clarified and address the concerns. BMJ Open: first published as /bmjopen on 16 May Downloaded from on 18 March 2019 by guest. Protected by copyright. 13