Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach

Ligang Hao; Junjie Zhang; Yonghui Di; Zheng Qi; Peng Zhang

doi:10.1371/journal.pone.0320674

Peer Review History

Original SubmissionMarch 10, 2024
10 Mar 2024 Author Response https://doi.org/10.1371/journal.pone.0320674.r001
10 Jan 2025 Decision Letter - Madhuradhar Chegondi, Editor PONE-D-24-07620Predicting Postoperative Venous Thromboembolism in Non-Small Cell Lung Cancer: A Stacking Machine Learning ApproachPLOS ONE Dear Dr. Di, 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. ============================== ACADEMIC EDITOR: Overall this is well written manuscript, however reviewers raised multiple comments. As one of the reviewers pointed out please explain the high rate of VTE in this cohort of patients. Is it related to any other uncaptured risk factors, as authors couldn't assess other gene mutations. Please add other potential gene mutations in the discussion which increases the VTE risk in this cohort. Reiewer1 recommended rejection and reviewer2 recommended major revision. As an academic editor, I feel this paper can add value to the existing literature and potentially can use the described ML methodology in VTE risk stratification. Please address reviewer 1 and 2 comments for further consideration of the manuscript publication. ============================== Please submit your revised manuscript by Feb 24 2025 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). 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Thank you for stating the following financial disclosure: This work was supported by the Key Development Plan of XingTai (ZC20301 to Junjie Zhang and 2022ZC271 to Ligang Hao). Please state what role the funders took in the study. If the funders had no role, please state: ""The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."" If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf. 5. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section. 6. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. [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: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: I Don't Know Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? 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Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: 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 authors report on predicting rates of VTE after thoracic surgery in patients with NSCLC. Issues with the paper include: 1. The VTE rate of 16% after surgery in a group of patients who received 4 wks of nadroparin prophylaxis is extraordinarily high. How do the authors account for such a high rate (even accounting for screening US and CT)? 2. The abstract, title etc should all mention that this is prediction of screen-detected VTE as a failure of thromboprophylaxis. This is not highlighted anywhere other than the Methods. 3. this is described as a machine learning paper, but it appears that EGFR mutation status was forced into the analysis. Is that correct? Or did the ML approach identify EGFR mutation status as a significant variable? 4. Extrapolation of these data to real world where screening is not typically done nor is 4 wks of thromboprophylaxis is difficult to ascertain. Reviewer #2: INTRODUCTION: suggest to reduce to one page METHODS: Line 113 to 114, please move to RESULTS portion. RESULTS: Patient Characteristics, line 163. Please mention a few highlights of the overall patient characteristics. For table 1, Please adjust decimal as appropriate also: round percentage to nearest tenth and present ages as whole numbers. DISCUSSION: Please summarize main findings of study into one paragraph. Line 250. How do the results for d dimer fit into this paragraph? 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Revision 1
8 Feb 2025 Author Response Dear Editor， We are truly grateful to yours and other reviewers’ critical comments and thoughtful suggestions on our manuscript (Predicting A Failure of Postoperative Thromboprophylaxis in Non-Small Cell Lung Cancer: A Stacking Machine Learning Approach). Based on these comments and suggestions, we have made careful modifications on the original manuscript. We hope the new manuscript will meet your magazine’s standard. You will find our point-by-point responses to the reviewers’ comments/ questions as following. Journal Requirements: 1. 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 https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf Thanks for the good advices from editors. We ensure that our manuscript meets PLOS ONE's style requirements, including those for file naming. 2. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Thanks for the good advices from editors. I have Update my Information. 3. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, all author-generated code must be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. Thanks for the good advices from editors. We have furtherly developed model online to ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. 4. Thank you for stating the following financial disclosure: Please state what role the funders took in the study. If the funders had no role, please state: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."" If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf. Thanks for the good advices from editors. This work was supported by the Key Development Plan of XingTai (ZC20301 to Junjie Zhang and 2022ZC271 to Ligang Hao). And we have added the statement in our cover letter. 5. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section. Thanks for the good advices from editors. we rechecked our manuscript that there was no ethics statement in other section. 6. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. Thanks for the good advices from editors. There was no Supporting Information file, and we state at the end of your manuscript. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: 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 report on predicting rates of VTE after thoracic surgery in patients with NSCLC. Issues with the paper include: 1. The VTE rate of 16% after surgery in a group of patients who received 4 wks of nadroparin prophylaxis is extraordinarily high. How do the authors account for such a high rate (even accounting for screening US and CT)? Thanks for the good advices from reviews. Previous study revealed that lung cancer is the most commonly identified malignancy in patients with VTE, with an incidence of 3%-13.9% in patients with VTE and 3.8% in patients with pulmonary embolism (PE). And incidence of 15.5% was reported in patients with lung resection, which was similar to our result. And much more stage III patients was enrolled in our study than previos study which also elevated the incidence of VTE. 2. The abstract, title etc should all mention that this is prediction of screen-detected VTE as a failure of thromboprophylaxis. This is not highlighted anywhere other than the Methods. Thanks for the good advices from reviews. We mention that this is prediction of screen-detected VTE as a failure of thromboprophylaxis in title and abstract. 3. this is described as a machine learning paper, but it appears that EGFR mutation status was forced into the analysis. Is that correct? Or did the ML approach identify EGFR mutation status as a significant variable? Thanks for the good advices from reviews. In our present study, EGFR mutation status was not forced into the analysis. It was identified as an independent risk factor by using univariable and multivariable analysis. 4. Extrapolation of these data to real world where screening is not typically done nor is 4 wks of thromboprophylaxis is difficult to ascertain. Thanks for the good advices from reviews. We pay much more attention to thromboprophylaxis since 2018. Every patients underwent surgery in our department was followed up every week to ensure that the screening and thromboprophylaxis was done under as the guidance of us. Reviewer #2: INTRODUCTION: suggest to reduce to one page. Thanks for the good advices from reviews. METHODS: Line 113 to 114, please move to RESULTS portion. Thanks for the good advices from reviews. we move it to RESULTS portion. RESULTS: Patient Characteristics, line 163. Please mention a few highlights of the overall patient characteristics. For table 1, Please adjust decimal as appropriate also: round percentage to nearest tenth and present ages as whole numbers. Thanks for the good advices from reviews. We mention a few highlights of the overall patient characteristics and adjust decimal round percentage to nearest tenth and present ages as whole numbers. DISCUSSION: Please summarize main findings of study into one paragraph. Thanks for the good advices from reviews. We summarize main findings of study into the last paragraph. Line 250. How do the results for d dimer fit into this paragraph? Thanks for the good advices from reviews. We recorrect that paragraph as following: In this study, the D-dimer levels were evaluated before surgery to reduce the influence of other factors as much as possible, so that it could reflect the hypercoagulable state of patients much more precisive. In this study, elevated D-dimer levels was also significantly related to VTE as an independent risk factor with OR=2.929 which was familiar to previous study. Any comparative literature that uses machine learning as well that have been validated? How does your model compare to validated ones? Please use past tense for completed actions and present tense for general validity. Thanks for the good advices from reviews. It was demonstrated that The model developed here fares better than previous machine learning models with an ROC AUC of 0.87 [39] and a C-index of 0.791-0.843 [40] in our manuscript. Thanks for the good advices from reviewers, we submitted it as a supplemental figure. Thanks for addressing the comments! We hope that these revisions are satisfactory and that the revised version will be acceptable for publication in PLOS ONE. Thank you very much for your work concerning our paper. Wish you all the best! Sincerely yours Attachments Attachment Submitted filename: responce letter2.docx https://doi.org/10.1371/journal.pone.0320674.r003
23 Feb 2025 Decision Letter - Madhuradhar Chegondi, Editor Predicting A Failure of Postoperative Thromboprophylaxis in Non-Small Cell Lung Cancer: A Stacking Machine Learning Approach PONE-D-24-07620R1 Dear Dr. Di 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 will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, 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, Madhuradhar Chegondi, MD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0320674.r004
Formally Accepted
Acceptance Letter - Madhuradhar Chegondi, Editor PONE-D-24-07620R1 PLOS ONE Dear Dr. Di, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, 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 customercare@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. Madhuradhar Chegondi Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0320674.r005

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