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Prediction of metastatic status in non-seminomatous testicular cancer. 2014

C G Ruf, and S Sachs, and N Khalili-Harbi, and H Isbarn, and W Wagner, and C Matthies, and V Meineke, and M Fisch, and F K Chun, and M Abend
Department of Urology, Federal Armed Forces Hospital, 22049, Hamburg, Germany, Dr.ChristianRuf@gmx.de.

OBJECTIVE 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. 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.

UI MeSH Term Description Entries
D008297 Male Males
D009373 Neoplasms, Germ Cell and Embryonal Neoplasms composed of primordial GERM CELLS of embryonic GONADS or of elements of the germ layers of the EMBRYO, MAMMALIAN. The concept does not refer to neoplasms located in the gonads or present in an embryo or FETUS. Germ Cell Cancer,Germ Cell Tumor,Neoplasms, Embryonal and Mixed,Cancer, Embryonal,Cancer, Embryonal and Mixed,Embryonal Neoplasms,Germ Cell Neoplasms,Germ Cell and Embryonal Neoplasms,Germ Cell and Embryonic Neoplasms,Neoplasms, Embryonal,Neoplasms, Germ Cell,Neoplasms, Germ Cell and Embryonic,Cancer, Germ Cell,Cancers, Embryonal,Cancers, Germ Cell,Embryonal Cancer,Embryonal Cancers,Embryonal Neoplasm,Germ Cell Cancers,Germ Cell Tumors,Neoplasm, Embryonal,Tumor, Germ Cell,Tumors, Germ Cell
D011379 Prognosis A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations. Prognostic Factor,Prognostic Factors,Factor, Prognostic,Factors, Prognostic,Prognoses
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012189 Retrospective Studies Studies used to test etiologic hypotheses in which inferences about an exposure to putative causal factors are derived from data relating to characteristics of persons under study or to events or experiences in their past. The essential feature is that some of the persons under study have the disease or outcome of interest and their characteristics are compared with those of unaffected persons. Retrospective Study,Studies, Retrospective,Study, Retrospective
D013736 Testicular Neoplasms Tumors or cancer of the TESTIS. Germ cell tumors (GERMINOMA) of the testis constitute 95% of all testicular neoplasms. Cancer of Testis,Cancer of the Testes,Testicular Cancer,Testicular Neoplasm,Testicular Tumor,Testis Cancer,Cancer of the Testis,Neoplasms, Testicular,Neoplasms, Testis,Testicular Tumors,Testis Neoplasms,Tumor of Rete Testis,Cancer, Testicular,Cancer, Testis,Cancers, Testicular,Cancers, Testis,Neoplasm, Testicular,Neoplasm, Testis,Rete Testis Tumor,Rete Testis Tumors,Testicular Cancers,Testis Cancers,Testis Neoplasm,Testis Tumor, Rete,Testis Tumors, Rete,Tumor, Testicular,Tumors, Testicular
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D018570 Risk Assessment The qualitative or quantitative estimation of the likelihood of adverse effects that may result from exposure to specified health hazards or from the absence of beneficial influences. (Last, Dictionary of Epidemiology, 1988) Assessment, Risk,Benefit-Risk Assessment,Risk Analysis,Risk-Benefit Assessment,Health Risk Assessment,Risks and Benefits,Analysis, Risk,Assessment, Benefit-Risk,Assessment, Health Risk,Assessment, Risk-Benefit,Benefit Risk Assessment,Benefit-Risk Assessments,Benefits and Risks,Health Risk Assessments,Risk Analyses,Risk Assessment, Health,Risk Assessments,Risk Benefit Assessment,Risk-Benefit Assessments

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