Peer Review History
Original SubmissionJanuary 27, 2020 |
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PONE-D-20-02468 Characterization of patients with advanced chronic pancreatitis based on electronic health data and high-throughput natural language processing of radiology reports. PLOS ONE Dear Dr. Wu, 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 following reviewers' comments and address them point by point. Please submit your revised manuscript by Jul 13 2020 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:
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We will update your Data Availability statement on your behalf to reflect the information you provide. 4. 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: Yes 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? 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: 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 ********** 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: In this paper, the authors present a retrospective cohort study including patients diagnosed with chronic pancreatitis (CP). To extract specific features from free-text radiology reports, a natural language processing (NLP) approach was developed and manually evaluated using a training set and a validation set, respectively. The algorithm was then applied on a large sets of reports, to define a subset of patients with advanced disease vs. other patients. As a main result, patients with advanced CP were at increased risk for pancreatic cancer-related mortality. Excess all-cause mortality was driven primarily by underweight BMI, smoking and diabetes. The use of NLP solutions to support retrospective research is an interesting topic, especially for those use-cases where relevant data is only contained in free text. Despite using a rule-based NLP approach, where concept variants might not be captured, evaluation results are promising. However, I believe there are a few points in the manuscript that could be extended or clarified. 1. In general, the section “Natural language processing for characterization of pancreatic imaging findings” would benefit from some clarification. Although more details are given in Appendix A, it would be helpful to briefly mention the high-level approach here, at least defining “search keywords”, “modifiers” and “exclusion terms” (especially considering that references to specific excluded terms are given). Were these keywords manually defined, or was there any data-driven step? Related to this, the authors refer to “further training of the computer-generated algorithm”. Was there any machine learning training involved? 2. Could the authors provide a few more details about the typical structure of documents? Do these usually contain predefined sections? How was spelling checking performed? More generally, do the authors think their approach could be easily reused or extended to process similar documents from a different institution? 3. I would suggest clarifying the section “NLP Performance evaluation” in Appendix A. Were results evaluated on a sentence level, report level, or patient level? This could be also clarified in the main manuscript. Also: could you please check the definitions of Specificity and NPV given here? 4. Did the authors perform any error analysis to identify particular issues with the developed NLP approach, e.g. how many false negatives were due to missing variants or misspellings? 5. The authors report p-values when comparing specific characteristics in advanced CP vs. other patients. Could they please clarify which tests were applied? 6. Table 3 reports causes of mortality in advanced CP vs. other patients. Could the authors clarify how these were defined? More specifically, is “Death from all causes” including all the causes listed below? If so, could you please check if reported sums are correct? Minor comments 7. I would suggest adding acronyms (NLP and CP) the first time they are mentioned in the text. 8. Please check the numbers in the following sentence (Pg. 9) vs. Table 3: “Frequency of pancreatic cancer-related death was increased among patients with advanced CP (6.9% vs. 5.2%, p<.001)..." Reviewer #2: The study aim in the abstract seems a bit too generic for the study, at least some more detail could be added here, like the focus on extracting the imaging features using NLP? Validation cohort: was this cohort also manually reviewed for the imaging findings? This is not explicitly mentioned in the methods section, however, seems to be required? It is a bit odd that the “Chronic Pancreatitis Study cohort” results paragraph comes second, whereas here the study cohort is presented? Any reason why this is not the first results paragraph? For figure 2 is the advanced diseases based on NLP extracted radiographic findings or is it based on manually curated findings? It would be good to make this explicit. Do the authors have any sense on how this algorithm would perform on external data from another hospital system? Are there any potential biases? It would be good to add this to the discussion. How is this approach generalizable to new problems in other diseases areas, e.g. cirrhosis or NASH in livers. Based on the appendix, it does seem that this approach is difficult to generalize, and scale to other problems. Can the authors comment on this and add this to the discussion? ********** 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.] 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. |
Revision 1 |
Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports. PONE-D-20-02468R1 Dear Dr. Wu, 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, Dejing Dou, Ph.D. 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 #3: 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 #3: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #3: 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 #1: No Reviewer #3: 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 #1: Yes Reviewer #3: 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 #1: (No Response) Reviewer #3: This paper develops a NLP algorithm to identify five specific features of patients with chronic pancreatitis from their radiology reports, and identify a subset of patients with advanced CP based on these features. The proposed method can be applied to other data sources with text and other medical conditions after modification. ********** 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 #3: No |
Formally Accepted |
PONE-D-20-02468R1 Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports. Dear Dr. Wu: 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 Professor Dejing Dou Academic Editor PLOS ONE |
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