Prospective metastatic risk assignment in clinical stage I nonseminomatous germ cell testis cancer: a single institution pilot study☆

Autor: Michael Perrotti, Robert E. Weiss, Anita Bancilla, Peter S. Amenta, Victor deCarvalho, Murali K. Ankem
Rok vydání: 2004
Předmět:
Zdroj: Urologic Oncology: Seminars and Original Investigations. 22:174-177
ISSN: 1078-1439
DOI: 10.1016/j.urolonc.2004.04.004
Popis: Objective: To gain initial experience with a histopathologic model to assign metastatic risk in patients with clinical stage I nonseminomatous germ cell testis cancer (CSI NSGCTC). Materials and methods: Histopathologic factors were recorded prospectively, and metastatic risk assigned according to the proposed model. In the model tested, percentage of embryonal carcinoma (%EMB) ≥80% and/or vascular invasion (+VI) denoted high (>50%) occult disease risk, while %EMB < 80% plus absence of VI denoted low (≤10%) risk. Risk stratification was correlated with outcome and assessed statistically. Results: There were 54 patients with CSI testis cancer evaluated during the study period. Patients with pure seminoma (n = 30), Sertoli cell tumor (n = 1), and Leydig cell tumor (n = 1) were excluded from analysis. Twenty-two patients had CSI NSGCTC and comprise the pilot study cohort. The median follow-up duration from the time of study entry is 31 months (range, 20–61 months). Utilizing the model tested, a statistically significant higher likelihood of occult disease in the high risk cohort compared to the low risk cohort was observed (67% vs. 0%; Fisher’s exact test, P = 0.005). Conclusions: The results of the present pilot study are encouraging, particularly in the potential of identifying a cohort at low metastatic risk. In the appropriate setting, such a patient might be considered for surveillance alone following orchiectomy. High risk assignment was associated with a positive predictive value (PPV) of 67%. This level of risk is superior to single factor PPV, and if confirmed, could influence clinical decision making. Further experience with this model in an expanded setting is required to establish its reproducibility and predictive value.
Databáze: OpenAIRE
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