An approach to estimating prognosis using fractional polynomials in metastatic renal carcinoma.
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.
Royston
P
P
MRC Clinical Trials Unit, Cancer Division, Medical Research Council (MRC), London, UK.
Reitz
M
M
Atzpodien
J
J
D000465:Algorithms; D002986:Clinical Trials as Topic; D005260:Female; D006801:Humans; D007167:Immunotherapy; D007680:Kidney Neoplasms / Q000188:drug therapy* / Q000401:mortality / Q000473:pathology; D008297:Male; D015233:Models, Statistical; D009362:Neoplasm Metastasis / Q000188:drug therapy*; D011379:Prognosis; D012307:Risk Factors; D016019:Survival Analysis