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Seventeen tool-development articles were included, mostly using national registry data, with limited external validation.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/prognostic-tools-for-older-women-with-breast-cancer-a-systematic-review/380443/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/prognostic-tools-for-older-women-with-breast-cancer-a-systematic-review/380443.png","ImageObject",300,407,{"name":42,"@type":43},"Terk","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-22","2026-09-24",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",6,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the purpose of this systematic review?","Question",{"text":63,"@type":64},"To systematically review prognostic models developed and/or validated for older patients with breast cancer, focusing on predictions of treatment response, recurrence, and mortality.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What sources and criteria were used to select studies?",{"text":68,"@type":64},"The review used a systematic search in three electronic databases and included original studies published before 8 November 2022 that developed and/or validated prognostic models for older breast cancer patients.",{"name":70,"@type":61,"acceptedAnswer":71},"How was the risk of bias and applicability assessed?",{"text":72,"@type":64},"The PROBAST tool was used to assess the risk of bias and applicability of each included prognostic tool.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},380443,1790751894,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,105,109,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":107,"slug":108},7,40,"healthcare",{"id":110,"doc_module":4,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},8,"Research & Report",30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":106,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145},1099525198933,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","medicina  \nSystematic Review  \nPrognostic Tools for Older Women with Breast Cancer: A Systematic Review  \nSydney M. Record 1, Tori Chanenchuk 1, Kendra M. Parrish 1, Samantha J. Kaplan 2, Gretchen Kimmick 3,4 and Jennifer K. Plichta 1,3,5, *  \nCitation: Record, S.M.; Chanenchuk, T.; Parrish, K.M.; Kaplan, S.J.; Kimmick, G.; Plichta, J.K. Prognostic Tools for Older Women with Breast Cancer: A Systematic Review. Medicina 2023, 59, 1576 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)medicina59091576  \nAcademic Editors: Jimmy T. Efird and Tithi Biswas  \nReceived: 19 July 2023  \nRevised: 23 August 2023  \nAccepted: 25 August 2023  \nPublished: 30 August 2023  \nCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA  \n2 Medical Center Library, Duke University, Durham, NC 27710, USA  \n3 Duke Cancer Institute, Duke University, Durham, NC 27710, USA  \n4 Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA  \n5 Department of Population Health Sciences, Duke University Medical Center, Durham, NC 27710, USA  \n* [Correspondence: jennifer.plichta@duke.edu](Correspondence: jennifer.plichta@duke.edu); Tel.: +1-919-681-9156; Fax: +1-919-660-8608  \nAbstract: Background: Breast cancer is the most common cancer in women, and older patients comprise an increasing proportion of patients with this disease. The older breast cancer population is heterogenous with unique factors affecting clinical decision making. While many models have been developed and tested for breast cancer patients of all ages, tools specifically developed for older patients with breast cancer have not been recently reviewed. We systematically reviewed prognostic models developed and/or validated for older patients with breast cancer. Methods: We conducted a systematic search in 3 electronic databases. We identified original studies that were published prior to 8 November 2022 and presented the development and/or validation of models based mainly on clinico-pathological factors to predict response to treatment, recurrence, and/or mortality in older patients with breast cancer. The PROBAST was used to assess the ROB and applicability of each included tool. Results: We screened titles and abstracts of 7316 records. This generated 126 studies for a full text review. We identified 17 eligible articles, all of which presented tool development. The models were developed between 1996 and 2022, mostly using national registry data. The prognostic models were mainly developed in the United States (n = 7; 41%) . For the derivation cohorts, the median sample size was 213 (interquartile range, 81–845) . For the 17 included modes, the median number of predictive factors was 7 (4.5–10) . Conclusions: There have been several studies focused on developing prognostic tools specifically for older patients with breast cancer, and the predictions made by these tools vary widely to include response to treatment, recurrence, and mortality. While external validation was rare, we found that it was typically concordant with interval validation results. Studies that were not validated or only internally validated still require external validation. However, most of the models presented in this review represent promising tools for clinical application in the care of older patients with breast cancer.  \nKeywords: prognostic tools; older; elderly; survival; prognosis  \n1. Introduction  \nBreast cancer is the most commonly diagnosed cancer with ~300,000 new diagnosesin 2022, and it is the second leading cause of cancer death among women worldwide [1] . Preventative screening through ","cbCaigUW42pl0AMB","https://ap.wps.com/l/cbCaigUW42pl0AMB","pdf",833066,18,"English","# Abstract\n## Introduction\n## Methods\n## Results\n## Conclusions","[{\"question\":\"What is the purpose of this systematic review?\",\"answer\":\"To systematically review prognostic models developed and/or validated for older patients with breast cancer, focusing on predictions of treatment response, recurrence, and mortality.\"},{\"question\":\"What sources and criteria were used to select studies?\",\"answer\":\"The review used a systematic search in three electronic databases and included original studies published before 8 November 2022 that developed and/or validated prognostic models for older breast cancer patients.\"},{\"question\":\"How was the risk of bias and applicability assessed?\",\"answer\":\"The PROBAST tool was used to assess the risk of bias and applicability of each included prognostic tool.\"}]","Prognostic Tools for Older Women with Breast Cancer - A Systematic Review | PDF",1790240187,45]