Predicting cancer-control outcomes in patients with renal cell carcinoma

Current Opinion in Urology

Volumn 17, Issue 5, 2007, Pages 295-302

  Karakiewicz, Pierre I ^a   Hutterer, Georg C ^a  

^a CENTRE HOSPITALIER DE L UNIVERSITÉ DE MONTRÉAL   (Canada)

Author keywords

Nomogram; Prognostic model; Recurrence; Renal cell carcinoma; Survival

Indexed keywords

CANCER GROWTH; CANCER RECURRENCE; CANCER STAGING; CANCER SURGERY; CANCER SURVIVAL; CLINICAL ASSESSMENT; HUMAN; KIDNEY CARCINOMA; MEDICAL DECISION MAKING; METASTASIS; NEPHRECTOMY; NOMOGRAM; PATIENT CARE; PREDICTIVE VALIDITY; PRIORITY JOURNAL; PROGNOSIS; REVIEW;

CARCINOMA, RENAL CELL; CHEMOTHERAPY, ADJUVANT; DECISION MAKING; DISEASE-FREE SURVIVAL; HUMANS; KIDNEY NEOPLASMS; MODELS, BIOLOGICAL; NEOPLASM STAGING; NEPHRECTOMY; NOMOGRAMS; PATIENT SELECTION; RECURRENCE; REPRODUCIBILITY OF RESULTS; TREATMENT OUTCOME;

EID: 34548304893     PISSN: 09630643     EISSN: None     Source Type: Journal    
DOI: 10.1097/MOU.0b013e3282a4a6b7     Document Type: Review

References (23)

1. Harrell FE, Califf RM, Pryor DB, et al. Evaluating the yield of medical tests. JAMA 1982; 247:2543-2546.
2. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15:361-387.
3. Karakiewicz PI, Briganti A, Chun FK, et al. Multiinstitutional validation of a new renal cancer-specific survival nomogram. J Clin Oncol 2007; 25:1316-1322. The authors demonstrate that the prediction of renal cancer-specific survival can be improved if traditional predictor variables are used within a prognostic nomogram.
4. Yaycioglu O, Roberts WW, Chan T, et al. Prognostic assessment of nonmetastatic renal cell carcinoma: a clinically based model. Urology 2001; 58:141-145.
5. Cindolo L, Patard JJ, Chiodini P, et al. Comparison of predictive accuracy of four prognostic models for nonmetastatic renal cell carcinoma after nephrectomy: a multicenter European study. Cancer 2005; 104:1362-1371.
6. Cindolo L, de la Taille A, Messina G, et al. A preoperative clinical prognostic model for nonmetastatic renal cell carcinoma. BJU Int 2003; 92:901-905.
7. Kattan MW, Reuter V, Motzer RJ, et al. A postoperative prognostic nomogram for renal cell carcinoma. J Urol 2001; 166:63-67.
8. Sorbellini M, Kattan MW, Snyder ME, et al. A postoperative prognostic nomogram predicting recurrence for patients with conventional clear cell renal cell carcinoma. J Urol 2005; 173:48-51.
9. Frank I, Blute ML, Cheville JC, et al. A multifactorial postoperative surveillance model for patients with surgically treated clear cell renal cell carcinoma. J Urol 2003; 170:2225-2232.
10. Zisman A, Pantuck AJ, Dorey F, et al. Improved prognostication of renal cell carcinoma using an integrated staging system. J Clin Oncol 2001; 19:1649-1657.
11. Zisman A, Pantuck AJ, Wieder J, et al. Risk group assessment and clinical outcome algorithm to predict the natural history of patients with surgically resected renal cell carcinoma. J Clin Oncol 2002; 20:4559-4566.
12. Han KR, Bleumer I, Pantuck AJ, et al. Validation of an integrated staging system toward improved prognostication of patients with localized renal cell carcinoma in an international population. J Urol 2003; 170:2221-2224.
13. Patard JJ, Kim HL, Lam JS, et al. Use of the University of California Los Angeles integrated staging system to predict survival in renal cell carcinoma: an international multicenter study. J Clin Oncol 2004; 22:3316-3322.
14. Frank I, Blute ML, Cheville JC, et al. An outcome prediction model for patients with clear cell renal cell carcinoma treated with radical nephrectomy based on tumor stage, size, grade and necrosis: the SSIGN score. J Urol 2002; 168:2395-2400.
15. Cagiannos I, Karakiewicz PI, Eastham JA, et al. A preoperative nomogram identifying decreased risk of positive pelvic lymph nodes in patients with prostate cancer. J Urol 2003; 170:1798-1803.
16. Motzer RJ, Mazumdar M, Bacik J, et al. Survival and prognostic stratification of 670 patients with advanced renal cell carcinoma. J Clin Oncol 1999; 17:2530-2540.
17. Motzer RJ, Bacik J, Murphy BA, et al. Interferon-alfa as a comparative treatment for clinical trials of new therapies against advanced renal cell carcinoma. J Clin Oncol 2002; 20:289-296.
18. Motzer RJ, Bacik J, Schwartz LH, et al. Prognostic factors for survival in previously treated patients with metastatic renal cell carcinoma. J Clin Oncol 2004; 22:454-463.
19. Karakiewicz PI, Trinh QD, Lam JS, et al. Platelet count and preoperative haemoglobin do not significantly increase the performance of established predictors of renal cell carcinoma-specific mortality. Eur Urol 2007 [epub ahead of print].
20. Kattan MW. Judging new markers by their ability to improve predictive accuracy. J Natl Cancer Inst 2003; 95:634-635.
21. Karakiewicz PI, Trinh QD, de la Taille A, et al. ECOG performance status 0 or 1 and symptom classification do not improve the ability to predict renal cell carcinoma-specific survival. Eur J Cancer 2007; 43:1023-1029.
22. Leibovich BC, Han KR, Bui MH, et al. Scoring algorithm to predict survival after nephrectomy and immunotherapy in patients with metastatic renal cell carcinoma: a stratification tool for prospective clinical trials. Cancer 2003; 98:2566-2575.
23. Leibovich BC, Cheville JC, Lohse CM, et al. A scoring algorithm to predict survival for patients with metastatic clear cell renal cell carcinoma: a stratification tool for prospective clinical trials. J Urol 2005; 174:1759-1763.