Protective effect of smoking cessation on subsequent myocardial infarction and ischemic stroke independent of weight gain: A nationwide cohort study

Jung-Hwan Cho; Hye-Mi Kwon; Se-Eun Park; Jin-Hyung Jung; Kyung-Do Han; Yong-Gyu Park; Yang-Hyun Kim; Eun-Jung Rhee; Won-Young Lee

doi:10.1371/journal.pone.0235276

Peer Review History

Original SubmissionJanuary 15, 2020
18 Mar 2020 Decision Letter - Michael Cummings, Editor PONE-D-20-01312 Protective effect of smoking cessation on subsequent myocardial infarction and ischemic stroke independent of weight gain: A nationwide cohort study PLOS ONE Dear Dr Lee, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Both reviewers commented on the large sample size and potential inherent in the analyses of these data. That said, both reviewers felt that analyses as presented were inadequate and need to be substantially revised before this paper can be considred for publication. The authors should heed the recommended changes in defining outcomes and presenting results if they are interested in revising this paper for consideration in PLOS ONE. 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We look forward to receiving your revised manuscript. Kind regards, Michael Cummings, PhD Academic Editor PLOS ONE Journal Requirements: 1. When submitting your revision, we need you to address these additional requirements. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: No Reviewer #2: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No Reviewer #2: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: No ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: No ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: 1. While the scale of this analysis which includes 5.2 million Korean adults is impressive neither the topic nor the results are novel. 2. The analytic approach is confusing and potentially flawed. The dependt variable of a 1-2 point change in BMI appears to be differential depending on an individual's height. For example, a 6 foot 1 inch individual demonstrating an 8 pound weight gain from 200 to 208 pounds would show a 1.0 change in BMI (from 26.4 to 27.4). Conversely a 5 foot 6 inch individual at a baseline weight of 120 pounds which show a 4.5 pound weight gain in order to achieve a 1.0 change in BMI (from 19.1 to 20.1). A much more straightforward approach to the analyses would have simply reported an overall change in weight rather than BMI. 3. Introduction: The text is very general and seems to overlook relative versus absolute effects of cardiac risk factors. The text does not include any information about affect sizes. Among all the risk factors identified smoking far and away is the most significant. 4. Study population: The exclusion of 17,000 individuals diagnosed with an MI or ischemic stroke within 1 year of follow-up is confusing. 5. Classification of the population into smokers and "those who had not smoked during this time" as non-smoker is confusing and inaccurate. Moreover, this approach is inconsistent with the common classification system noting individuals as current, former or never smokers. 6. table 1. What is "difference" under systolic blood pressure, diastolic blood pressure, fasting plasma glucose, total cholesterol? 7. Table 2. Body mass index is not weight gain. Adding additional variables into their multivariate models parens alcohol, income, exercise, hypertension, diabetes, hyperlipidemia) does not change risk estimates beyond more parsimonious models. Authors are urged to simplify their models and descriptions. 8. Table 3. The results and conclusions would be much easier to understand if they were presented as actual weight gains rather than changes in BMI. 8. Supporting information is confusing. Figure 1 raises additional questions about the study design since it suggests that BMI was assessed over an interval of 4 years prior to baseline while MI and ischemic strokes were assessed for a period of 5 years after baseline. Content of figure 2 is also unclear. 9. As a minor point the manuscript would benefit from careful editing to clarify wording and grammar. Reviewer #2: Introduction 1. The first sentence of the second paragraph is confusing. Consider rewording. 2. Consider rewording the second sentence to "Clair et al. [8] showed that body weight change after smoking cessation....." 3. Explain what you mean by "mortality seems better in higher BMI groups" Methods Study population: 4. Correct the following sentence"Our study approved by the NHIS" to "Our study WAS approved by the NHIS" 5. Correct "4 years ago" to "4 years PRIOR" in line 77/78 6. Correct "Individuals diagnosed with previous MIs or ISs" to "Individuals PREVIOUSLY DIAGNOSED with MIs or ISs" 7. Correct "We further excluded 17,192 patients who diagnosed with MI or IS..." to "We further excluded 17,192 patients who WERE diagnosed with MI or IS..." 8. Explain why 17,192 who were diagnosed with MI or MS were excluded. What was unclear about the causal relationship? 9. Excluding patients with the outcome without further explanation contributes to selection bias. Definition of smoking history and outcomes: 10. Replace "years ago" with "years prior" 11. Explain what you mean by "self-questionnaire". Do you mean self-report? 12. How did you define "steadily smoking"? Consider adding the actual questions that were asked to this section. Same for those who quit. 13. State the follow-up period in this section. 14. This sentence in unclear "The exclusion criteria for previous MIs or ISs were the same as above." State clearly what the exclusion criteria were. Other baseline characteristics: 15. Include sex and age in this section. Statistical analysis: 16. It is unclear whether this was a primary or secondary data analysis. 17. Incidence rates are obtained by a Binomial/Poisson regression, Risk Differences are obtained by a normal/log-normal regression, and hazard ratios are obtained by time-to-even regression. These are all different models assessing different measures. Please explain which procedure was used to obtain which measure and what the exposure and outcome were for each procedure. Also, explain whether or not models were adjusted, and if so, the variables that were adjusted for. Table 1: 18. Indicate which variables are shown as N(%) and which are shown as Mean (SD). 19. Add a column fourth for the total and percentages for smoking status. 20. Replace "Number" by "Characteristic" and "No. (%)" by "N (%)". 21. Footnote: use lower case "p" indicating p-value. 22. What do you mean by "All characteristics met P < 0.0001"? What is being being tested here? Please specify. 23. Add the proportion of daily and non-daily smokers to Table 1. Pack years cannot be calculated for non-daily smokers. Table 2: 24. Consider changing the reference group to current smokers. 25. Was the incidence rate adjusted or not? Table 3: 26. Consider changing the reference group to current smokers. 27. Was the incidence rate adjusted or not? 28. It would be worthwhile to perform the regression of the outcomes on BMI (4 categories) stratified by smoking status adjusting for all identified confounders except BMI. Results 29. Please do not use risk ratio and hazard ratio interchangeably, RR does not take into effect the time to event while HR does. Discussion 30. Be aware of overarching statements or statements that are not supported by evidence such as the first 2 sentences of the discussion. 31. This paper did not assess the effect of BMI on the risk of MS and IS as mentioned in the second paragraph of the discussion, however, this would be possible with the analyses that I previously suggested under table 3. 32. Discussion will likely have to be revised according to the suggested analyses. General: 33. Consider restricting the analysis to those who are 40 years of age or older as incidence of cardiovascular outcomes are likely to be low in the younger age groups. 34. Specify the novelty of this article and what value it adds to the existing literature. 35. Figure 2 does not add any more information than Table 3, consider removing. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. 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Revision 1
1 May 2020 Author Response Here are the responses to the comments of the reviewers: To reviewer #1 1. While the scale of this analysis which includes 5.2 million Korean adults is impressive neither the topic nor the results are novel. : Thank you for your comment. Although there have been various studies before our study on the relationship between weight gain after smoking cessation and cardiovascular disease, we demonstrated significant results by evaluating the occurrence of real cardiovascular events as outcome in millions of people including both sexes across the country, complementing the shortcomings of these studies. 2. The analytic approach is confusing and potentially flawed. The dependt variable of a 1-2 point change in BMI appears to be differential depending on an individual's height. For example, a 6 foot 1 inch individual demonstrating an 8 pound weight gain from 200 to 208 pounds would show a 1.0 change in BMI (from 26.4 to 27.4). Conversely a 5 foot 6 inch individual at a baseline weight of 120 pounds which show a 4.5 pound weight gain in order to achieve a 1.0 change in BMI (from 19.1 to 20.1). A much more straightforward approach to the analyses would have simply reported an overall change in weight rather than BMI. : Thank you for your comment. Based on your feedback, we’ve conducted a new analysis with a straightforward approach using weight, not BMI. As a result, it is consistently confirmed that weight gain after smoking cessation does not adversely affect the cardiovascular protection effect. 3. Introduction: The text is very general and seems to overlook relative versus absolute effects of cardiac risk factors. The text does not include any information about affect sizes. Among all the risk factors identified smoking far and away is the most significant. : Thank you for your comment. We also agree that smoking cessation is the most effective and powerful factor for reducing the risk of cardiovascular disease. We’ve revised the text so that the relative risk is not overestimate relative to the absolute risk of smoking. 4. Study population: The exclusion of 17,000 individuals diagnosed with an MI or ischemic stroke within 1 year of follow-up is confusing. : Thank you for your comment. We initially thought it was unclear whether a casual relationship existed between the incidence of myocardial infarctions or strokes within one year from baseline and exposure to weight change. However, we agree that you were confused with this approach. We’ve included all MIs and ISs that occurred after the baseline without a one-year washout period in the analyses. 5. Classification of the population into smokers and "those who had not smoked during this time" as non-smoker is confusing and inaccurate. Moreover, this approach is inconsistent with the common classification system noting individuals as current, former or never smokers. : Thank you for your comment. We evaluated the subjects’ smoking history through self-questionnaires during health screenings including their current smoking status, duration, and amount of smoking. The participants responded to their current smoking status through one of three choices: never smoked, smoking in the past but now quitting, or continuing to smoke. Current smokers were defined as those who responded to smoke continuously from 4 years prior to baseline. Those who consistently never smoked were classified as non-smokers. The participants who quit smoking at baseline, but who were smokers 4 years prior were classified as the smoking cessation group. We’ve added these to the text to avoid confusion of communication. 6. table 1. What is "difference" under systolic blood pressure, diastolic blood pressure, fasting plasma glucose, total cholesterol? : Thank you for your comment. The "difference" of these characteristics refers to the numerical change of the baseline and the 4 year prior. For example, systolic (1.0 ± 16.1 mmHg) and diastolic blood pressure (0.3 ± 11.5 mmHg), blood cholesterol (5.5 ± 34.7 mg/dl), and fasting blood sugar (5.1 ± 26.0 mg/dl) increased in the smoking cessation group at baseline compared to the 4 year prior. 7. Table 2. Body mass index is not weight gain. Adding additional variables into their multivariate models parens alcohol, income, exercise, hypertension, diabetes, hyperlipidemia) does not change risk estimates beyond more parsimonious models. Authors are urged to simplify their models and descriptions. : Thank you for your comment. In the selection of confounders in our study, we selected variables that influence the cardiovascular outcomes. We agree that chronic disease such as hypertension, diabetes, and hyperlipidemia are not appropriate to be included as variables under the influence of weight gain. We’ve subtracted these mediators from variables, and instead presented a subgroup analysis with or without mediators. 8. Table 3. The results and conclusions would be much easier to understand if they were presented as actual weight gains rather than changes in BMI. : Thank you for your comment. As we answered in comment #2, we’ve conducted a new analysis using actual weight gains. 9. Supporting information is confusing. Figure 1 raises additional questions about the study design since it suggests that BMI was assessed over an interval of 4 years prior to baseline while MI and ischemic strokes were assessed for a period of 5 years after baseline. Content of figure 2 is also unclear. : Thank you for your comment. As you said, weight change was assessed over an interval of 4 years prior (2005~2006) to baseline (2009 ~ 2010). MI and ischemic strokes were followed up from baseline (2009 ~ 2010) to the end of 2015, and the mean follow-up periods for MI and ischemic strokes were 5.9 ± 0.7 years and 5.8 ± 0.8 years, respectively. We’ve modified figure 1 and deleted figure 2. 10. As a minor point the manuscript would benefit from careful editing to clarify wording and grammar. : We thank you for pointing out this and have tried to clarify wording and correct the English grammar to improve communication. To reviewer #2 1. The first sentence of the second paragraph is confusing. Consider rewording. : Thank you for your comment. We’ve reworded the first sentence of the second paragraph which can be confusing. 2. Consider rewording the second sentence to "Clair et al. [8] showed that body weight change after smoking cessation....." : Thank you for your comment. We’ve reworded the second sentence to “In the study using cohort data from the Framingham Offspring Study...” 3. Explain what you mean by "mortality seems better in higher BMI groups" : Thank you for your comment. Cardiovascular prognosis and mortality seems better in overweight or obese described by the “obesity paradox”. This means that the risk of actual cardiovascular events due to weight gain might be underestimated when determining mortality as an outcome. As a result of the study by Hu Y et al. mentioned in that section, recent quitters that did not gain weight had a higher risk of mortality relative to those who gained weight. Methods Study population: 4. Correct the following sentence"Our study approved by the NHIS" to "Our study WAS approved by the NHIS" : Thank you for your comment. We’ve corrected it as your comment. 5. Correct "4 years ago" to "4 years PRIOR" in line 77/78 : Thank you for your comment. We’ve corrected it as your comment. 6. Correct "Individuals diagnosed with previous MIs or ISs" to "Individuals PREVIOUSLY DIAGNOSED with MIs or ISs" : Thank you for your comment. We’ve corrected it as your comment. 7. Correct "We further excluded 17,192 patients who diagnosed with MI or IS..." to "We further excluded 17,192 patients who WERE diagnosed with MI or IS..." : Thank you for your comment. We’ve removed this sentence from the text. 8. Explain why 17,192 who were diagnosed with MI or MS were excluded. What was unclear about the causal relationship? : Thank you for your comment. We initially thought it was unclear whether a casual relationship existed between the incidence of myocardial infarctions or strokes within one year from baseline and exposure to weight change. However, we agree that you and reviewer #1 were confused with this approach. We’ve included all MIs and ISs that occurred after the baseline without a one-year washout period in the analyses. 9. Excluding patients with the outcome without further explanation contributes to selection bias. : Thank you for your comment. Since our study made the first diagnosed cardiovascular disease as an outcome, the participants who were previously diagnosed with cardiovascular disease could not be included in the study. In addition, people with a history of cardiovascular disease could have unintentional weight loss and/or sarcopenia. This can be a bias to the weight change after smoking cessation, an exposure of our study. Definition of smoking history and outcomes: 10. Replace "years ago" with "years prior" : Thank you for your comment. We replaced it with "years prior". 11. Explain what you mean by "self-questionnaire". Do you mean self-report? : Thank you for your comment. “Self-questionnaire" are questions that must be answered in a medical examination. Questions on current smoking status, duration, and amount of smoking are written in the questionnaire. The participants responded to their current smoking status through one of three choices: never smoked, smoking in the past but now quitting, or continuing to smoke. 12. How did you define "steadily smoking"? Consider adding the actual questions that were asked to this section. Same for those who quit. : Thank you for your comment. The participants responded to their current smoking status through one of three choices: never smoked, smoking in the past but now quitting, or continuing to smoke. Current smokers were defined as those who responded to smoke continuously from 4 years prior to baseline. Those who consistently never smoked were classified as non-smokers. The participants who quit smoking at baseline, but who were smokers 4 years prior were classified as the smoking cessation group. We’ve added these to the text to avoid confusion of communication. 13. State the follow-up period in this section. : Thank you for your comment. We’ve written a follow-up period in this section. The mean follow-up periods for MI and ischemic strokes were 5.9 ± 0.7 years and 5.8 ± 0.8 years, respectively. 14. This sentence in unclear "The exclusion criteria for previous MIs or ISs were the same as above." State clearly what the exclusion criteria were. : Thank you for your comment. The occurrence of a MI was defined as an ICD-10 I21 or I22 code claimed at least twice, or more than once with a hospitalization. The occurrence of an IS was defined as an ICD-10 I63 or I64 code claimed together with a hospitalization and a radiological examination (magnetic resonance imaging or computed tomography). The participants who had a history of MI or IS identified using these ICD code claims prior to baseline were excluded. We've updated this in the text. Other baseline characteristics: 15. Include sex and age in this section. : Thank you for your comment. We’ve written statements about age and sex in this section. Statistical analysis: 16. It is unclear whether this was a primary or secondary data analysis. : Thank you for your comment. We’ve corrected the paragraph so that the primary and secondary analyses are not confused. 17. Incidence rates are obtained by a Binomial/Poisson regression, Risk Differences are obtained by a normal/log-normal regression, and hazard ratios are obtained by time-to-even regression. These are all different models assessing different measures. Please explain which procedure was used to obtain which measure and what the exposure and outcome were for each procedure. Also, explain whether or not models were adjusted, and if so, the variables that were adjusted for. : Thank you for your comment. The incidence rates were expressed as crude rates without statistical test analysis. HRs in primary and secondary analyses were analyzed using a Cox proportional hazards model with a 95% confidence interval (CI). We’ve added a description of variables used for adjustment in each model to the text. Table 1: 18. Indicate which variables are shown as N(%) and which are shown as Mean (SD). : Thank you for your comment. We’ve inserted N(%) and Mean(SD) in Table 1, which are appropriate for each characteristics. 19. Add a column fourth for the total and percentages for smoking status. : Thank you for your comment. We’ve added the number of subjects in each group, along with the percentages of the total. 20. Replace "Number" by "Characteristic" and "No. (%)" by "N (%)". : Thank you for your comment. The "number" we entered was the number of subjects in each group in the row. We’ve modified "No. (%)" to "N (%)". 21. Footnote: use lower case "p" indicating p-value. : Thank you for your comment. We replaced uppercase P by lowercase. 22. What do you mean by "All characteristics met P < 0.0001"? What is being being tested here? Please specify. : Thank you for your comment. This indicates that there are significant differences in characteristics of the three groups according to smoking history. The difference between the three groups is significant, even if only one comparison of the three groups is significant. 23. Add the proportion of daily and non-daily smokers to Table 1. Pack years cannot be calculated for non-daily smokers. : Thank you for your comment. Unfortunately, the daily and non-daily smokers cannot be distinguished from the questionnaire used in the medical examination, so this may be a limitation of our study. We describe this 'point prevalence' design in the limitation section of the discussion. Table 2: 24. Consider changing the reference group to current smokers. : Thank you for your comment. HRs were compared among the smoking cessation, non-smoker, and current-smoker groups with current smokers as a reference group. If the meaning of this comment needs to be modified "1 (Ref.)", we will revise it as soon as you respond. 25. Was the incidence rate adjusted or not? : Thank you for your comment. The incidence rates were expressed as crude rates without adjustment. Table 3: 26. Consider changing the reference group to current smokers. : Thank you for your comment. HRs were compared among the smoking cessation, non-smoker, and current-smoker groups with current smokers as a reference group. If the meaning of this comment needs to be modified "1 (Ref.)", we will revise it as soon as you respond. 27. Was the incidence rate adjusted or not? : Thank you for your comment. The incidence rates were expressed as crude rates without adjustment. 28. It would be worthwhile to perform the regression of the outcomes on BMI (4 categories) stratified by smoking status adjusting for all identified confounders except BMI. : Thank you for your comment. We agreed with reviewer # 1's comment #2, so we've conducted a new analysis with a straightforward approach using weight, not BMI. Therefore, baseline BMI has been included in variables. Results 29. Please do not use risk ratio and hazard ratio interchangeably, RR does not take into effect the time to event while HR does. : Thank you for your comment. We have fixed the risk ratio to the hazard ratio as your opinion. Discussion 30. Be aware of overarching statements or statements that are not supported by evidence such as the first 2 sentences of the discussion. : Thank you for your comment. We’ve tried to reduce exaggerated expressions that are not supported by evidence. 31. This paper did not assess the effect of BMI on the risk of MS and IS as mentioned in the second paragraph of the discussion, however, this would be possible with the analyses that I previously suggested under table 3. : Thank you for your comment. As we responded to your comment #28, we’ve conducted a new analysis using weight. 32. Discussion will likely have to be revised according to the suggested analyses. : Thank you for your comment. We’ve added related contents to the discussion. General: 33. Consider restricting the analysis to those who are 40 years of age or older as incidence of cardiovascular outcomes are likely to be low in the younger age groups. : Thank you for your comment. We agree with your comment and have restricted the research group to those over 40 years of age. The results are consistent after restriction. 34. Specify the novelty of this article and what value it adds to the existing literature. : Thank you for your comment. Although there have been various studies before our study on the relationship between weight gain after smoking cessation and cardiovascular disease, we demonstrated significant results by evaluating the occurrence of real cardiovascular events as outcome in millions of people including both sexes across the country, complementing the shortcomings of these studies. 35. Figure 2 does not add any more information than Table 3, consider removing. : Thank you for your comment. We’ve retained Table 3 and removed figure 2. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0235276.r002
12 Jun 2020 Decision Letter - Michael Cummings, Editor Protective effect of smoking cessation on subsequent myocardial infarction and ischemic stroke independent of weight gain: A nationwide cohort study PONE-D-20-01312R1 Dear Dr. Lee, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Michael Cummings, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #2: No ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #2: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #2: (No Response) ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #2: No https://doi.org/10.1371/journal.pone.0235276.r003
Formally Accepted
6 Jul 2020 Acceptance Letter - Michael Cummings, Editor PONE-D-20-01312R1 Protective effect of smoking cessation on subsequent myocardial infarction and ischemic stroke independent of weight gain: A nationwide cohort study Dear Dr. Lee: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Michael Cummings Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0235276.r004

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