T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers

Zatil Zahidah Sharani; Nurhuda Ismail; Siti Munira Yasin; Muhamad Rodi Isa; Asmah Razali; Mas Ahmad Sherzkawee; Ahmad Izuanuddin Ismail

doi:10.1371/journal.pone.0287374

Peer Review History

Original SubmissionSeptember 16, 2022
22 Nov 2022 Decision Letter - Yuvaraj Krishnamoorthy, Editor PONE-D-22-25828T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokersPLOS ONE Dear Dr. Ismail, 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. Please submit your revised manuscript by Jan 06 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. 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If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide. [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: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 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: Yes ****** 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: Yes ****** 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: The manuscript is well conceived and written and needs some major revisions to be acceptable for publication. Major Concerns: 1. There is no reporting of how well the model performed in the internal validation cohort. 2. The HOsmer-Lemeshow is not a reliable test for calibration, authors should present calibration plots as illustrated in the TRIPOD statement for reporting of risk prediction models. 3. Early in the paper it is not clearly and consistently articulated that a simple binary indicator of 'loss to follow-up (LTFUP)' is the outcome being modeled. It is confusing with all the information presented on different outcome states. is the outcome LTFUP relative to the occurrence of all other outcome types? 4. cross-sectional: the study uses fixed, baseline values of predictors to calculate the occurrence of LTFUP, which happen at some point in the future, so the repeated use of cross-sectional seems not quite accurate 5. On line 29 no statement about how much data is missing, whether it can be assumed to be missing at random, and whether any form of imputation was used. If not, how was this justified? 6. Process of multivariable model selection should be in the stats section rather than in results. 7. On line 188 test of equality for two AUC values should use DeLong's test rather than chi-square. 8. The tiny fraction of women in the study suggests these results should be limited to males only. Minor comments: 1. multivariable instead of multivariate when modeling a single outcome. 2. AUC provides fair, not good, discrimination. 3. Line 134 confusing. 4. lines 187-8, chi-square not appropriate for comparing two AUC. 5. line 220: need to define RM2160 which presumably is transparent to Malaysians. 6. Line 244 - state 14 variables retained but only 13 listed. 7. line 260: no mention of model performance in validation cohort. 8. lines 282-3: no comprehensive discussion or treatment of missingness 9. lines 288-9: that chi-square test does suggest anything about missing values being completely at random. 10. Table 5: okay to present Hosmer-Lemeshow as supplement to calibration plots. 11. line 351: need to define IVDU ****** 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? 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Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0287374.r001
Revision 1
11 Jan 2023 Author Response Major Concerns: 1 There is no reporting of how well the model performed in the internal validation cohort. Reports on the performance of the internal validation cohort is available in the results section under the performance of final model. 2 The HOsmer-Lemeshow is not a reliable test for calibration, authors should present calibration plots as illustrated in the TRIPOD statement for reporting of risk prediction models: As per suggestion, calibration plots have been added in addition to the Hosmer-Lemeshow value for the model calibration reporting. The calibration curve for the final model and the internal validation model are available in Fig 3 and Fig 4. 3 Early in the paper it is not clearly and consistently articulated that a simple binary indicator of 'loss to follow-up (LTFUP)' is the outcome being modeled. It is confusing with all the information presented on different outcome states. is the outcome LTFUP relative to the occurrence of all other outcome types? The outcome being measured and modelled in this study is the LTFU. The LTFU outcome is being compared with the successful TB outcome (cured and completed treatment) 4 Cross-sectional: the study uses fixed, baseline values of predictors to calculate the occurrence of LTFUP, which happen at some point in the future, so the repeated use of cross-sectional seems not quite accurate: We have look back at the methods of this study. We agree that the term “cross-sectional study” used in this study is inappropriate. This study involves secondary data analysis of a cohort of TB patients from year 2013-2017 in the national TB database. We looked back at the predictors that lead to the LTFU outcome. Thus, the correct study design for this study would be a retrospective cohort study. 5 On line 29 no statement about how much data is missing, whether it can be assumed to be missing at random, and whether any form of imputation was used. If not, how was this justified? Additional statement on the missing data information has been added in the abstract and result section. We have run the missing value analysis and the little MCAR test to report on the data missingness. Certain variable in the database has been recategorized and subsequent changes on the results and figure has been amended. 6 Process of multivariable model selection should be in the stats section rather than in results: The paragraph on variable selection for the final model has been changed to the methodology section under the statistical analysis part. 7 On line 188 test of equality for two AUC values should use DeLong's test rather than chi-square: As per suggestion we have analyse the performance between the two-model using the DeLong’s test. The outcome of this test is included under the result section in the performance of the final model paragraph. 8 The tiny fraction of women in the study suggests these results should be limited to males only: The prevalence of woman who smokes in our country based on the latest national health morbidity survey (NHMS, 2015) is 1.3% which correspond to our finding in this study. Thus, we choose to remain the female subject in this study. Besides that, gender was not a significant predictor in this study, therefore the small proportion of female gender do not affect the performance of the model. Minor comments: 1 Multivariable instead of multivariate when modeling a single outcome: The term multivariate used in this manuscript has been changed to multivariable throughout the manuscript. 2 AUC provides fair, not good, discrimination: Correction has been made. The term used on the AUC has been changed to fair discrimination. 3 Line 134 confusing: The sentence has been rearranged. The outcome being measured in this study is the LTFU TB outcome. 4 Lines 187-8, chi-square not appropriate for comparing two AUC: As per suggestion we have analyse the performance between the two-model using the DeLong’s test. The outcome is available under the result section. 5 line 220: need to define RM2160 which presumably is transparent to Malaysians: The categorization used for the income level is according to the median personal income for the population of Selangor state based on the department of statistic Malaysia (DOSM, 2018). Details on this variable has been added under the statistical analysis paragraph. 6 Line 244 - state 14 variables retained but only 13 listed: We have corrected the sentence. The correct number of variables included in the multivariable analysis were 14, and 12 were retained in the final model. 7 line 260: no mention of model performance in validation cohort: The performance of the Internal validation model was mentioned under the result section in the performance of the final model paragraph. 8 lines 282-3: no comprehensive discussion or treatment of missingness Management and reports on the missing data has been included in the result section under the prognostic scoring system for LTFU paragraph. 9 lines 288-9: that chi-square test does suggest anything about missing values being completely at random: We have conducted the missing value analysis and the little’s MCAR test to handle the missing data in the database. The report on the chi-square test has been corrected. 10 Table 5: okay to present Hosmer-Lemeshow as supplement to calibration plots: Calibration curve for both final and internal validation model has been plotted under Fig 3A and Fig 3B in the manuscript using GGplot R statistical package. 11 line 351: need to define IVDU IVDU has been defined as intravenous drug user in the sentence. Thank you Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0287374.r002
8 May 2023 Decision Letter - Yuvaraj Krishnamoorthy, Editor PONE-D-22-25828R1T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokersPLOS ONE Dear Dr. Ismail, 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. Please submit your revised manuscript by Jun 22 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Yuvaraj Krishnamoorthy Academic Editor PLOS ONE [Note: HTML markup is below. Please do not edit.] 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 #1: All comments have been addressed Reviewer #2: (No Response) ******** 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 #1: Yes Reviewer #2: (No Response) ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: (No Response) ****** 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 #1: Yes Reviewer #2: (No Response) ****** 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 #1: Yes Reviewer #2: (No Response) ****** 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 #1: The authors have done a nice job responding to all my previous concerns. I advise acceptance with minor revisions and do not need to see the manuscript again. 1. On line 51 put a comma in 835,000. 2. re-vise line 178 as follows: ' ... with LTFU were analyed using ... ' 3. revise line 183 as ' For the monthly income level, the cutpoint at ... (488.30 USD) was based on ... ' 4. Line 227: homogeneous 5. In Fig 2 lease add the labelled AUC for each curve. 6. For Fig 3 recommend confidence limits for blue model performance to show overlap with diagonal. Reviewer #2: Authors intended to develop a prognostic scoring tool in predicting loss to follow-up (LTFU) among TB smoking patients. The constructed scoring was based on T-BACCO SCORE and predicted the risk for LTFU with low-, medium- and high-risk. The results showed a fair discrimination, good calibration. 1. The outcome is loss to follow-up. What’s the length of follow-up time for each individual? Are they very different or the same across the individuals? If vary, will this confound the results? 2. Line 179. The significance level was set to be 0.025. Please explain why this threshold is selected? 3. Line 194. AUC of 0.5 is selected as a discrimination threshold. However, 0.5 is just the value with random classification. Will such a low threshold be a concern? 4. Line 199. De Long test was used to compare the AUC between models. Please clarify what two models were compared? development and the internal validation cohort? If so, does it really make sense to compare their AUC when they are using different data? 5. It’s good to see the missingness doesn’t differ between development cohort and internal validation cohort. However, shouldn’t the missing data be taken care before split the sample into two cohorts? ****** 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 #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.] 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. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0287374.r003
Revision 2
18 May 2023 Author Response Response to Reviewers Dear PLOS One Editors, AMENDMENT TO THE MANUSCRIPT ENTITLED “T-BACCO SCORE: A PREDICTIVE SCORING TOOL FOR TUBERCULOSIS(TB) LOSS TO FOLLOW-UP AMONG TB SMOKERS Response to Reviewer 1: 1 On line 51 put a comma in 835,000 Response: Correction has been made accordingly on-line 51 2 Revise line 178 as follows: ' ... with LTFU were analysed using ... ' Response: The sentence has been corrected on line 178 “with LTFU were analysed using a simple logistic regression analysis”. 3 Revise line 183 as ' For the monthly income level, the cut point at ... (488.30 USD) was based on ... ' Response: The cut of point at RM2160 (488.30 USD) used was based on the median personal income of population in this country according to the department of statistics Malaysia in 2018 (DOSM). 4 Line 227: homogeneous Response: Spelling correction has been made accordingly, from “homogenous” to “homogeneous”. 5 In Fig 2 please add the labelled AUC for each curve. Response: Amendment has been made in Fig 2. AUC value for each curve has been added. 6 For Fig 3 recommend confidence limits for blue model performance to show overlap with diagonal. Response: Calibration curve Fig 3(A) and Fig 3(B) has been amended. The confidence limits each calibration curve was inserted as per-recommendation. Response to Reviewer 2: 1 The outcome is loss to follow-up. What’s the length of follow-up time for each individual? Are they very different or the same across the individuals? If vary, will this confound the results? Response: The length of follow-up time unlikely confound the results. Majority of each individual follow-up duration is limited to the recommended six-month of TB treatment duration. Patients with TB MDR status (who needs longer treatment duration) has been excluded from the databased. 2 Line 179. The significance level was set to be 0.025. Please explain why this threshold is selected? Response: For variable selection into the multiple logistic regression analysis, significance level was set at 0.25 (not 0.025). This threshold was selected to ensure that adequate variable can be considered in the final logistic model. 3 Line 194. AUC of 0.5 is selected as a discrimination threshold. However, 0.5 is just the value with random classification. Will such a low threshold be a concern? Response: We are aware that AUC of 0.5 indicates no discrimination and AUC 0.7 is considered acceptable. However, in clinical setting within the TB domain especially on LTFU issue an AUC more than 0.6 is considered satisfactory as compared to the common acceptable threshold of 0.7. We have revised the sentence in line 194 to “AUC value ranges from 0.5 to 1, where a greater AUC value indicates that the model has better ability to distinguish patients who were LTFU and had successful TB treatment outcome”. 4 Line 199. De Long test was used to compare the AUC between models. Please clarify what two models were compared? development and the internal validation cohort? If so, does it really make sense to compare their AUC when they are using different data? Response: Thank you for your comment. Yes, the two model that were compared are the development and the internal validation cohort. Initially, De Long test was used to inform that the performance between the two model has not much difference. However, after careful reading, we realized that De Long test is used to compare two correlated model. Therefor this analysis will be removed from this study finding. The comparison of the ROC between the two cohort will be assessed based on their overlapping confidence interval: Development cohort: 0.681 (95% CI 0.657-0.713) Internal validation cohort: 0.668 (95% CI 0.639-0.698) 5 It’s good to see the missingness doesn’t differ between development cohort and internal validation cohort. However, shouldn’t the missing data be taken care before split the sample into two cohorts? Response: We agreed that missing data analysis should be managed earlier, however the two cohort (development and the internal validation) are coming from the same source of data based and it was divided randomly, therefor it should not be a concern. The purpose of analysing the missing data separately is to provide a more representative picture on the data missingness for each cohort to the reader. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0287374.r004
5 Jun 2023 Decision Letter - Yuvaraj Krishnamoorthy, Editor T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers PONE-D-22-25828R2 Dear Dr. Ismail, 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, Yuvaraj Krishnamoorthy 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 #1: All comments have been addressed 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 #1: Yes Reviewer #2: (No Response) ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: (No Response) ****** 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 #1: No Reviewer #2: (No Response) ****** 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 #1: Yes Reviewer #2: (No Response) ****** 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 #1: (No Response) 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 #1: No Reviewer #2: No ******** https://doi.org/10.1371/journal.pone.0287374.r005
Formally Accepted
8 Jun 2023 Acceptance Letter - Yuvaraj Krishnamoorthy, Editor PONE-D-22-25828R2 T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers Dear Dr. Ismail: 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. Yuvaraj Krishnamoorthy Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0287374.r006

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