{"title":"Identifying Optimal Candidates for Primary Tumor Resection Among Metastatic Pancreatic Cancer Patients: A Population-Based Predictive Model.","authors":"Kaifeng Su, Ruifeng Duan, Yang Wu","doi":"10.1080/07357907.2024.2349585","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>There is a controversy about whether surgery should proceed among metastatic pancreatic cancer (mPC) patients. A survival benefit was observed in mPC patients who underwent primary tumor resection; however, determining which patients would benefit from surgery is complex. For this purpose, we created a model to identify mPC patients who may benefit from primary tumor excision.</p><p><strong>Methods: </strong>Patients with mPC were extracted from the Surveillance, Epidemiology, and End Results database, and separated into surgery and nonsurgery groups based on whether the primary tumor was resected. Propensity score matching (PSM) was applied to balance confounding factors between the two groups. A nomogram was developed using multivariable logistic regression to estimate surgical benefit. Our model is evaluated using multiple methods.</p><p><strong>Results: </strong>About 662 of 14,183 mPC patients had primary tumor surgery. Kaplan-Meier analyses showed that the surgery group had a better prognosis. After PSM, a survival benefit was still observed in the surgery group. Among the surgery cohort, 202 patients survived longer than 4 months (surgery-beneficial group). The nomogram discriminated better in training and validation sets under the receiver operating characteristic (ROC) curve (AUC), and calibration curves were consistent. Decision curve analysis (DCA) revealed that it was clinically valuable. This model is better at identifying candidates for primary tumor excision.</p><p><strong>Conclusion: </strong>A helpful prediction model was developed and validated to identify ideal candidates who may benefit from primary tumor resection in mPC.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"333-344"},"PeriodicalIF":1.8000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Investigation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/07357907.2024.2349585","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/7 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: There is a controversy about whether surgery should proceed among metastatic pancreatic cancer (mPC) patients. A survival benefit was observed in mPC patients who underwent primary tumor resection; however, determining which patients would benefit from surgery is complex. For this purpose, we created a model to identify mPC patients who may benefit from primary tumor excision.
Methods: Patients with mPC were extracted from the Surveillance, Epidemiology, and End Results database, and separated into surgery and nonsurgery groups based on whether the primary tumor was resected. Propensity score matching (PSM) was applied to balance confounding factors between the two groups. A nomogram was developed using multivariable logistic regression to estimate surgical benefit. Our model is evaluated using multiple methods.
Results: About 662 of 14,183 mPC patients had primary tumor surgery. Kaplan-Meier analyses showed that the surgery group had a better prognosis. After PSM, a survival benefit was still observed in the surgery group. Among the surgery cohort, 202 patients survived longer than 4 months (surgery-beneficial group). The nomogram discriminated better in training and validation sets under the receiver operating characteristic (ROC) curve (AUC), and calibration curves were consistent. Decision curve analysis (DCA) revealed that it was clinically valuable. This model is better at identifying candidates for primary tumor excision.
Conclusion: A helpful prediction model was developed and validated to identify ideal candidates who may benefit from primary tumor resection in mPC.
期刊介绍：
Cancer Investigation is one of the most highly regarded and recognized journals in the field of basic and clinical oncology. It is designed to give physicians a comprehensive resource on the current state of progress in the cancer field as well as a broad background of reliable information necessary for effective decision making. In addition to presenting original papers of fundamental significance, it also publishes reviews, essays, specialized presentations of controversies, considerations of new technologies and their applications to specific laboratory problems, discussions of public issues, miniseries on major topics, new and experimental drugs and therapies, and an innovative letters to the editor section. One of the unique features of the journal is its departmentalized editorial sections reporting on more than 30 subject categories covering the broad spectrum of specialized areas that together comprise the field of oncology. Edited by leading physicians and research scientists, these sections make Cancer Investigation the prime resource for clinicians seeking to make sense of the sometimes-overwhelming amount of information available throughout the field. In addition to its peer-reviewed clinical research, the journal also features translational studies that bridge the gap between the laboratory and the clinic.
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