Trial reportBritish journal of cancer1999
Modelling the effects of standard prognostic factors in node-positive breast cancer. German Breast Cancer Study Group (GBSG).
Trial report in British journal of cancer, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed.
- Non-linear transformations of age at diagnosis, tumor size, and number of positive lymph nodes in prediction of clinical outcome in breast cancer.BMC cancer · 2018Trial
- No socioeconomic inequalities in colorectal cancer survival within a randomised clinical trial.British journal of cancer · 2008Trial
- Is treatment with interferon-alpha effective in all patients with metastatic renal carcinoma? A new approach to the investigation of interactions.British journal of cancer · 2004Trial
- Multimodal machine learning integrates clinical and comorbidity data to predict breast cancer prognosis and treatment outcomes.Scientific reports · 2026Article
- A decomposition of Fisher's information to inform sample size for developing or updating fair and precise clinical prediction models - part 2: time-to-event outcomes.Diagnostic and prognostic research · 2025Article
- On the 12th Day of Christmas, a Statistician Sent to Me . . .BMJ (Clinical research ed.) · 2022Article
- Optimal designs for health risk assessments using fractional polynomial models.Stochastic environmental research and risk assessment : research journal · 2022Article
- Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer.Saudi journal of biological sciences · 2022Article
- Article
- A flexible and robust method for assessing conditional association and conditional concordance.Statistics in medicine · 2019Article
- Multiple imputation for discrete data: Evaluation of the joint latent normal model.Biometrical journal. Biometrische Zeitschrift · 2019Article
- Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): An Abridged Explanation and Elaboration.Journal of the National Cancer Institute · 2018Review
- Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example.PloS one · 2016Article
- Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration.BMC medicine · 2012Article
- Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): explanation and elaboration.PLoS medicine · 2012Article
- Ratio between positive lymph nodes and total excised axillary lymph nodes as an independent prognostic factor for overall survival in patients with nonmetastatic lymph node-positive breast cancer.Indian journal of surgical oncology · 2010Article
- Estimation and external validation of a new prognostic model for predicting recurrence-free survival for early breast cancer patients in the UK.British journal of cancer · 2010Article
- Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study.BMC medical research methodology · 2010Article
- Ratio between positive lymph nodes and total excised axillary lymph nodes as an independent prognostic factor for overall survival in patients with nonmetastatic lymph node-positive breast cancer.Indian journal of surgical oncology · 2010Article
- Impact of GnRH ovarian stimulation protocols on intracytoplasmic sperm injection outcomes.Reproductive biology and endocrinology : RB&E · 2009Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prognostic models that predict the clinical course of a breast cancer patient are important in oncology. We propose an approach to constructing such models based on fractional polynomials in which useful transformations of the continuous factors are determined. The idea may be applied with all types of regression model, including Cox regression, the method of choice for survival-time data. We analyse a prospective study of node-positive breast cancer. Seven standard prognostic factors--age, menopausal status, tumour size, tumour grade, number of positive lymph nodes, progesterone and oestrogen receptor concentrations--were investigated in 686 patients, of whom 299 had an event for recurrence-free survival and 171 died. We determine a final model with transformations of prognostic factors and compare it with the more traditional approaches using categorized variables or assuming a straight line relationship. We conclude that analysis using fractional polynomials can extract important prognostic information which the traditional approaches may miss.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.