Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patients: A Korean Gynecologic Oncology Group ancillary study

Dong-hoon Jang; Hyun-Gyu Lee; Banghyun Lee; Sokbom Kang; Jong-Hyeok Kim; Byoung-Gie Kim; Jae-Weon Kim; Moon-Hong Kim; Xiaojun Chen; Jae Hong No; Jong-Min Lee; Jae-Hoon Kim; Hidemich Watari; Seok Mo Kim; Sung Hoon Kim; Seok Ju Seong; Dae Hoon Jeong; Yun Hwan Kim

doi:10.1371/journal.pone.0305360

Peer Review History

Original SubmissionJanuary 23, 2024
7 May 2024 Decision Letter - Ahmed Mohamed Maged, Editor PONE-D-23-43861Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patientsPLOS 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. ============================== ACADEMIC EDITOR: Please respond to all comments point by point ============================== Please submit your revised manuscript by Jun 21 2024 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. 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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: Partly Reviewer #2: Partly Reviewer #3: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: 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 Reviewer #2: Yes Reviewer #3: 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 Reviewer #2: Yes Reviewer #3: 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 main objective of this study is to exted the current criteria for FST in endometrial cancer, but the population in the study includes woman in post-menopause. I am afraid that the study population does not reflect the final population that the study is aimed at; can you better argue this aspect? Reviewer #2: The manuscript is well written and interesting, addressing the important issue of identifying candidates with low-risk endometrial cancer and the possibility to preserve fertility. As a radiologist, I find nothing specifically to comment on. The MRI methods are described in previous papers from the KGOG. The present paper describes advanced mathematical methods on preoperative assessment for prediction of postoperative pathology to help extend the current criteria for fertility sparing therapy, which was found to be difficult. The AUC was found to be highest for machine learning NPM2, however only moderately higher in Group 1, 2 and 4, and in fact lower in Group 3. As the authors write, larger studies are needed to confirm the results. Thus, I suggest a more humble Conclusion inserting the word "somewhat" and "may": On the other hand, the NPMs using Machine Learning provided a somewhat better prediction than conventional analysis. NPMs may help... Reviewer #3: Thanks to today's technologies, prediction model studies such as those in this article are now very popular, and I think they provide very successful prediction (mostly). Therefore, considering how useful these prediction models are in the field of health, I think this article should definitely be included in the journal. Frankly, very good statistics have been made and it has been turned into a nice article. ****** 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: Yes: Henrik Leonhardt Reviewer #3: Yes: OMER DEMIR ******** [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. Attachments Attachment Submitted filename: Manuscript.docx https://doi.org/10.1371/journal.pone.0305360.r001
Revision 1
20 May 2024 Author Response Editor: An interesting well designed study. Some issues need clarifications 1. Add type of the study to the title � The following words were added to the title: Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patients: a Korean Gynecologic Oncology Group ancillary study. 2. More details about inclusion and exclusion criteria are needed as women with other malignancies associated comorbidities ...........etc � The inclusion criteria were already mentioned in detail as follows: The inclusion criteria were no MI or MI <1/2 on preoperative MRI and endometrioid adenocarcinoma and grades 1 or 2 on the endometrial biopsy. � This study did not have exclusion criteria. This study examined the relationship between the preoperative assessment and postoperative final pathology depending on the presence or absence of MI and grades 1 or 2 in patients with low-risk endometrial cancer (EC) on a preoperative assessment using the data from the KGOG 2015. Therefore, other factors, such as other malignancies associated with comorbidities, etc., did not have an influence on the results of this study. Therefore, exclusion criteria were not required. � Exclusion criteria of the KGOG 2015 were as follows: patients with histologic features suggesting squamous cell carcinoma or carcinosarcoma on preoperative biopsy; inadequate imaging study; no lymph node dissection; and sarcoma (reference 6 in this study). � Therefore, the following sentence was added: The inclusion criteria were... ; there were no exclusion criteria. 3. Trial registration details � The following words and contents were added: In KGOG 2015, between January 1, 2012, and December 31, 2014, 529 consecutive EC patients underwent a preoperative assessment based on MRI, an endometrial biopsy, and serum CA 125 testing, followed by surgical staging, including systemic pelvic and para-aortic lymphadenectomy [6]. In this prospective, multicenter cohort study, the participants were enrolled in 20 hospitals in three countries (Korea, Japan, and China) between January 2012 and December 2014. Approval from local institutional review boards was obtained for each center. Each participating center was a tertiary hospital that regularly provided surgical care for EC and had multidisciplinary teams that included specialized gynecologic oncologists, pathologists, and radiologists. The inclusion criteria were as follows: 1) EC, 2) no deep MI (MI <1/2) on MRI, 3) no enlarged lymph nodes on MRI, 4) no suspicious extrauterine spread, and 5) serum CA 125 < 35 U/mL. Patients with squamous cell carcinoma or carcinosarcoma on a preoperative biopsy, inadequate imaging study, no lymph node dissection, or sarcoma were excluded. The 2009 FIGO classification was used for the stage based on the final pathological findings. 4. Sample size calculation need to be explained in more details � In this study, the sample size was not calculated. All patients who were eligible for the inclusion criteria were included. � Processes to select total eligible patients and four individual groups were already provided in the manuscript in detail as follows: two hundred and fifty-one eligible patients were selected from the KGOG 2015 dataset according to the inclusion criteria, which were no MI or MI <1/2 on preoperative MRI and endometrioid adenocarcinoma and grades 1 or 2 on the endometrial biopsy. Then, the eligible patients for this study were assigned to four groups. Group 1 included patients with no MI on preoperative MRI and grade 1 on an endometrial biopsy. Group 2 included patients with no MI on preoperative MRI and grade 2 on an endometrial biopsy. Group 3 included patients with MI <1/2 on preoperative MRI and grade 1 on an endometrial biopsy. Group 4 included patients with MI <1/2 on preoperative MRI and grade 2 on an endometrial biopsy. 5. please add what the study adds to the existing knowledge and the future recommendations in details � This study already provided ‘what the study adds to the existing knowledge’ in details as follows: 1. a prediction of the postoperative pathology was ineffective in low-risk EC patients classified according to the presence or absence of MI and grade 1 or 2 on the preoperative assessment; 2. because the NPMs using Machine Learning have a somewhat better prediction than conventional analysis, NPMs may help select more eligible patients for FST among low-risk EC patients. � The following words were added to ‘the future recommendations’: These NPMs and their outcomes should be confirmed in well-designed, large-scale prospective studies of premenopausal women. Reviewer #1: The main objective of this study is to exted the current criteria for FST in endometrial cancer, but the population in the study includes woman in post-menopause. I am afraid that the study population does not reflect the final population that the study is aimed at; can you better argue this aspect? � In this study, 39.4% of the population were premenopausal women, and 60.6% of the population were postmenopausal women. The average age of women diagnosed with endometrial cancer is 60. Endometrial cancer affects commonly postmenopausal women and between 15% and 25% of EC are found in premenopause [reference 14 in this study]. Therefore, it is difficult to investigate the study with only premenopausal women because of the low incidence of endometrial cancer in premenopausal women. � Recently, some studies have reported the difference between pre- and postmenopausal women with endometrial cancer. One study reported that women who were postmenopausal had worse tumor pathological gradings, more severe muscular invasion, and a higher rate of lymphatic metastasis. These factors led to a higher demand for postoperative radiotherapy in patients but a lower survival rate (reference: Lyu YL, et al., Transl Cancer Res. 2023 Mar 31;12(3):595–604). Another study reported that premenopausal women more often had ‘low’ risk disease (78% vs. 46%, p < 0.001). Among sonographic and anthropometric features, only an irregular endometrial-myometrial border was associated with ‘intermediate/high’ risk compared to ‘low risk’ in premenopausal women. Conversely, in postmenopausal women, multiple features are correlated with ‘intermediate/high’ risk disease. These findings emphasize the importance of considering menopausal status when evaluating sonographic features in women with endometrial cancer (Green RW, et al., Diagnostics (Basel), 2023, Dec 19;14(1):1). � To our knowledge, there is no evidence that in endometrial cancer, pathologic findings (endometrioid type or grade) or MRI findings differ between premenopausal women and postmenopausal women or are diagnosed by different criteria. � Therefore, we think that the composition of premenopausal and postmenopausal women might have only a minimal influence on the significance of this study to predict final pathology depending on preoperative myometrial invasion (MRI) and grade assessment (endometrial biopsy) in low-risk endometrial cancer patients. � However, our results need to be confirmed in the premenopausal population. � Therefore, the following sentences were added to limitations: Third, this study included premenopausal (39.4%) and postmenopausal (60.6%) women despite the objective of this study being to extend the current criteria for FST in EC. On the other hand, EC commonly affects postmenopausal women, and the incidence of EC in premenopausal women is low (15–25%) [14]. Therefore, it is difficult to conduct the study with only premenopausal women. Moreover, there is no evidence that in EC, the pathology findings (endometrioid type or grade) or MRI findings differ between premenopausal women and postmenopausal women or are diagnosed by different criteria. Therefore, the composition of premenopausal and postmenopausal women might only have a minimal influence on the significance of this study to predict final pathology depending on preoperative MRI and grade assessment (endometrial biopsy) in low-risk EC patients. Reviewer #2: The manuscript is well written and interesting, addressing the important issue of identifying candidates with low-risk endometrial cancer and the possibility to preserve fertility. As a radiologist, I find nothing specifically to comment on. The MRI methods are described in previous papers from the KGOG. The present paper describes advanced mathematical methods on preoperative assessment for prediction of postoperative pathology to help extend the current criteria for fertility sparing therapy, which was found to be difficult. The AUC was found to be highest for machine learning NPM2, however only moderately higher in Group 1, 2 and 4, and in fact lower in Group 3. As the authors write, larger studies are needed to confirm the results. Thus, I suggest a more humble Conclusion inserting the word "somewhat" and "may": On the other hand, the NPMs using Machine Learning provided a somewhat better prediction than conventional analysis. NPMs may help... � The following words were inserted according to reviewer’ suggestion: On the other hand, the NPMs using Machine Learning provided a somewhat better prediction than conventional analysis. NPMs may help select more eligible patients for FST among low-risk EC patients. Memos in manuscript: 1. Introduction: ………….‘‘low-risk’’ population. Please provide references to the literature to support this statement � References 2–5 were added. Therefore, in the entire manuscript, the number of references was changed. 2. Materials and Methods; 3.1.1. Data Preprocessing: First, missing values were identified in the preoperative tumor size (largest diameter). Can you justify why did you have missing data about this parameter? � Unfortunately, we cannot clearly explain the reasons for the missing values occurrence in tumor size (largest diameter) on preoperative MRI because KGOG 2015 did not mention ‘preoperative tumor size (largest diameter)’ in its published article (reference 6 in this study). � This study was an ancillary study of KGOG 2015, which was a prospective, multicenter cohort study performed between January 1, 2012, and December 31, 2014. In KGOG 2015, all participating centers (20 hospitals in three countries) were tertiary hospitals that regularly provided surgical care for endometrial cancer and had multidisciplinary teams including specialized gynecologic oncologists, pathologists, and radiologists (reference 6 in this study). Because KGOG 2015 was a trial performed before 10 years, we cannot ask the radiologists the reasons. Therefore, we just guess that adequate MRI findings might have been provided by radiologists, but very small tumor sizes (< 1cm) might not have been reported. � We hope that you will understand this situation. Can you quantify how many missing value imputed with mean post-operative value? � The number of missing values was already provided as the findings of the preoperative MRI in Table 1. All missing values were imputed with the mean post-operative value. � Therefore, the following words were added to the sentence: First, missing values were identified in the preoperative tumor size (largest diameter) (Table 1). All these missing values were imputed with mean postoperative tumor size values……………… Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0305360.r002
30 May 2024 Decision Letter - Ahmed Mohamed Maged, Editor Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patients: a Korean Gynecologic Oncology Group ancillary study PONE-D-23-43861R1 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 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, Ahmed Mohamed Maged, MD 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: Yes ****** 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: Yes: Henrik Leonhardt ******** https://doi.org/10.1371/journal.pone.0305360.r003
Formally Accepted
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