Prediction of metastatic status in non-seminomatous testicular cancer.

PURPOSE

To examine the significance of 90 biomarkers for predicting metastatic status in non-seminomatous germ cell tumors (NSGCT). By predicting metastatic status, it may be possible to eliminate unnecessary therapeutic or diagnostic efforts.

MATERIALS AND METHODS

We investigated 552 males who were diagnosed with non-metastatic (n = 273) and metastatic (n = 279) NSGCT between 2000 and 2011. The sample included cancers of different histologies: embryonal cell carcinoma (n = 131), teratoma (n = 55), and mixed histology (n = 366). We collected and analyzed more than 90 parameters via logistic regression: demographic characteristics, medical history, histopathological parameters, and levels of tumor markers and hormones.

RESULTS

Testis histology (p = 0.004), clinical symptoms (p = 0.0005), tumor length (p = 0.005), infiltration of the rete testis (p = 0.008), invasion of lymphatic (pL1) and blood vessels (pV1) (p < 0.0001), and levels of enzymes such as LDH, βHCG, AFP, and FSH (p values as small as <0.0001) were associated with metastatic status. With one model, we identified 14 out of 76 (18.4 %) metastatic NSGCT cases with 93-100 % certainty (positive predictive value) at 99 % specificity by the peripheral blood levels of LDH (day of operation) in combination with FSH measurements (1 day after operation). A second model included pV, tumor length, and FSH (1 day after operation). It identified 25 out of 90 (27.8 %) non-metastatic NSGCT with approximately 90 % certainty (negative predictive value) at 94-98 % sensitivity.

CONCLUSIONS

No single parameter was able to discriminate metastatic from non-metastatic NSGCT, but combinations of parameters in two predictive models accurately identified the metastatic status in 23 % of the cases in our sample.