当前位置： SCI文献检索 > JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY期刊下所有文献 > A clinician's guide for developing a prediction model: a case study using real-world data of patients with castration-resistant prostate cancer.

A clinician's guide for developing a prediction model: a case study using real-world data of patients with castration-resistant prostate cancer.

Abstract：

PURPOSE:With the increasing interest in treatment decision-making based on risk prediction models, it is essential for clinicians to understand the steps in developing and interpreting such models. METHODS:A retrospective registry of 20 Dutch hospitals with data on patients treated for castration-resistant prostate cancer was used to guide clinicians through the steps of developing a prediction model. The model of choice was the Cox proportional hazard model. RESULTS:Using the exemplary dataset several essential steps in prediction modelling are discussed including: coding of predictors, missing values, interaction, model specification and performance. An advanced method for appropriate selection of main effects, e.g. Least Absolute Shrinkage and Selection Operator (LASSO) regression, is described. Furthermore, the assumptions of Cox proportional hazard model are discussed, and how to handle violations of the proportional hazard assumption using time-varying coefficients. CONCLUSION:This study provides a comprehensive detailed guide to bridge the gap between the statistician and clinician, based on a large dataset of real-world patients treated for castration-resistant prostate cancer.

journal_name

J Cancer Res Clin Oncol

journal_title

Journal of cancer research and clinical oncology

authors

Veen KM,de Angst IB,Mokhles MM,Westgeest HM,Kuppen M,Groot CAU,Gerritsen WR,Kil PJM,Takkenberg JJM

doi

10.1007/s00432-020-03286-8

subject

Has Abstract

pub_date

2020-08-01 00:00:00

pages

2067-2075

issue

8

eissn

0171-5216

issn

1432-1335

pii

10.1007/s00432-020-03286-8

journal_volume

146

pub_type

杂志文章,评审

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