建立霍奇金淋巴瘤胸部放射治疗女性乳腺癌绝对风险预测模型。

IF 1 4区数学 Q3 STATISTICS & PROBABILITY

Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2025-01-03 eCollection Date: 2025-03-01 DOI:10.1093/jrsssc/qlae063

Sander Roberti, Flora E van Leeuwen, Michael Hauptmann, Ruth M Pfeiffer

{"title":"建立霍奇金淋巴瘤胸部放射治疗女性乳腺癌绝对风险预测模型。","authors":"Sander Roberti, Flora E van Leeuwen, Michael Hauptmann, Ruth M Pfeiffer","doi":"10.1093/jrsssc/qlae063","DOIUrl":null,"url":null,"abstract":"We built models to predict absolute breast cancer (BC) risk in women treated with radiotherapy for Hodgkin lymphoma (HL). We first estimated relative risks (RRs) for risk factors, including radiation dose to 10 breast segments to accommodate heterogeneity of treatment effects, using a case-control sample nested in an HL survivor cohort. To estimate RRs of case-control matching factors we developed novel weighting approaches. We then combined RRs with age-specific BC incidence and competing mortality rates from the HL survivor cohort and a population-based registry, accommodating differences between them. We compared the performance of models using segment-specific doses with using mean dose only.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"74 2","pages":"466-490"},"PeriodicalIF":1.0000,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905882/pdf/","citationCount":"0","resultStr":"{\"title\":\"Building absolute breast cancer risk prediction models for women treated with chest radiation for Hodgkin lymphoma.\",\"authors\":\"Sander Roberti, Flora E van Leeuwen, Michael Hauptmann, Ruth M Pfeiffer\",\"doi\":\"10.1093/jrsssc/qlae063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We built models to predict absolute breast cancer (BC) risk in women treated with radiotherapy for Hodgkin lymphoma (HL). We first estimated relative risks (RRs) for risk factors, including radiation dose to 10 breast segments to accommodate heterogeneity of treatment effects, using a case-control sample nested in an HL survivor cohort. To estimate RRs of case-control matching factors we developed novel weighting approaches. We then combined RRs with age-specific BC incidence and competing mortality rates from the HL survivor cohort and a population-based registry, accommodating differences between them. We compared the performance of models using segment-specific doses with using mean dose only.\",\"PeriodicalId\":49981,\"journal\":{\"name\":\"Journal of the Royal Statistical Society Series C-Applied Statistics\",\"volume\":\"74 2\",\"pages\":\"466-490\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2025-01-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905882/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Royal Statistical Society Series C-Applied Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1093/jrsssc/qlae063\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Royal Statistical Society Series C-Applied Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1093/jrsssc/qlae063","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}

引用次数: 0

摘要

我们建立了模型来预测接受放射治疗的霍奇金淋巴瘤（HL）女性患乳腺癌（BC）的绝对风险。我们首先估算了风险因素的相对风险（rr），包括对10个乳腺节段的辐射剂量，以适应治疗效果的异质性，使用了一个嵌套在HL幸存者队列中的病例对照样本。为了估计病例对照匹配因素的rr，我们开发了新的加权方法。然后，我们将rr与来自HL幸存者队列和基于人群的登记的年龄特异性BC发病率和竞争死亡率相结合，以适应它们之间的差异。我们比较了使用分段特定剂量和仅使用平均剂量的模型的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Building absolute breast cancer risk prediction models for women treated with chest radiation for Hodgkin lymphoma.

We built models to predict absolute breast cancer (BC) risk in women treated with radiotherapy for Hodgkin lymphoma (HL). We first estimated relative risks (RRs) for risk factors, including radiation dose to 10 breast segments to accommodate heterogeneity of treatment effects, using a case-control sample nested in an HL survivor cohort. To estimate RRs of case-control matching factors we developed novel weighting approaches. We then combined RRs with age-specific BC incidence and competing mortality rates from the HL survivor cohort and a population-based registry, accommodating differences between them. We compared the performance of models using segment-specific doses with using mean dose only.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of the Royal Statistical Society Series C-Applied Statistics 数学-统计学与概率论

CiteScore

2.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The Journal of the Royal Statistical Society, Series C (Applied Statistics) is a journal of international repute for statisticians both inside and outside the academic world. The journal is concerned with papers which deal with novel solutions to real life statistical problems by adapting or developing methodology, or by demonstrating the proper application of new or existing statistical methods to them. At their heart therefore the papers in the journal are motivated by examples and statistical data of all kinds. The subject-matter covers the whole range of inter-disciplinary fields, e.g. applications in agriculture, genetics, industry, medicine and the physical sciences, and papers on design issues (e.g. in relation to experiments, surveys or observational studies). A deep understanding of statistical methodology is not necessary to appreciate the content. Although papers describing developments in statistical computing driven by practical examples are within its scope, the journal is not concerned with simply numerical illustrations or simulation studies. The emphasis of Series C is on case-studies of statistical analyses in practice.