An approach to estimating prognosis using fractional polynomials in metastatic renal carcinoma.
Br J Cancer
We present a prognostic model for metastatic renal cell carcinoma based on fractional polynomials. We retrospectively analysed 425 metastatic renal cell carcinoma patients treated with subcutaneous recombinant cytokine-based home therapies in consecutive trials. In our approach, we categorised a continuous prognostic index produced by the multivariable fractional polynomial (MFP) algorithm, using a strategy in which continuous predictors are kept continuous. The MFP algorithm selected five prognostic factors as significant at the 5% level in a multivariable model: lymph node metastases, liver metastases, bone metastases, age, C-reactive protein and neutrophils. The MFP model allowed us to divide patients into four risk groups achieving median overall survivals of 38 months (low risk), 23 months (low intermediate risk), 15 months (high intermediate risk) and 5.6 months (high risk). Our approach, based on categorising a continuous prognostic index produced by the MFP algorithm, allowed more flexibility in the determination of risk groups than traditional approaches.
|Title:||An approach to estimating prognosis using fractional polynomials in metastatic renal carcinoma.|
|Keywords:||Algorithms, Clinical Trials as Topic, Female, Humans, Immunotherapy, Kidney Neoplasms, Male, Models, Statistical, Neoplasm Metastasis, Prognosis, Risk Factors, Survival Analysis|
|UCL classification:||UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > MRC Clinical Trials Unit at UCL
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