Prognostic significance of the mode of detection in renal tumours.
OBJECTIVE
To evaluate the mode of detection of 400 renal tumours as a prognostic factor compared with the usual clinical and pathological prognostic variables.


METHODS
The data were reviewed for 400 patients operated for a renal tumour at our institution between 1984 and 1999, analysing the prognostic value of age, sex, tumour size, stage, grade, vein invasion, adrenal gland invasion, lymph node invasion, metastasis, and mode of detection (incidental or not). The survival rates were assessed using the Kaplan-Meier method and log-rank test, and the data evaluated using multivariate analysis with the Cox proportional-hazard model.


RESULTS
In all, 151 (38%) renal tumours were discovered incidentally. There was no significant difference in the percentage of renal cell carcinoma found between the groups of patients discovered incidentally or not (94.4% vs 93.9%). Tumours were smaller in the incidental group (5.7 cm vs 8.7 cm, P < 0.001). In the incidental group, 15.2% of the tumours were treated with partial nephrectomy, against 1.2% in the symptomatic group (P < 0.001). The specific survival was significantly better in patients with renal tumours discovered incidentally (log-rank test, P < 0.001). The multivariate analysis showed that the mode of detection, stage, grade, metastasis (all P < 0.001), and lymphatic extension (P = 0.005) were independent prognostic factors.


CONCLUSIONS
The incidental discovery of renal tumours gives a supplementary benefit to patients in terms of survival, and should be considered as a prognostic factor in addition to stage and grade.
Patard
J-J
JJ
Department of Urology and Pathology, CHU Rennes, France. jean-jacques.patard@chu-rennes.fr
Rodriguez
A
A
Rioux-Leclercq
N
N
Guillé
F
F
Lobel
B
B
D002292:Carcinoma, Renal Cell / Q000175:diagnosis*; D016009:Chi-Square Distribution; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007680:Kidney Neoplasms / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D016019:Survival Analysis