Prognostic factors in advanced ovarian carcinoma. 1986

J R Redman, and G R Petroni, and P E Saigo, and N L Geller, and T B Hakes

Nineteen factors were analyzed for prognostic significance in a series of 89 women with advanced (stage III or IV) ovarian carcinoma treated with chemotherapy after initial debulking surgery. Seventy-eight of these women received cyclophosphamide, Adriamycin (Adria Laboratories, Columbus, Ohio), and cisplatin (CAP) treatment, and 11 received cyclophosphamide initially with Adriamycin and cisplatin administered at the time of recurrence. Median survival and remission duration were 25 and 19 months, respectively. Using survival as an end point, significant prognostic factors in univariate analyses included the total residual mass after debulking (P = .0007), largest residual mass after debulking (P = .0008), and stage (P = .0098). Using remission duration as an end point, significant prognostic factors in univariate analyses included total residual mass after debulking (P = .007) and the largest residual mass after debulking (P = .0020). The prognostic variables were then considered as possible predictors of survival in a multivariate analysis using the Cox proportional hazards model resulting in the following expression: lambda i(t)/lambda o(t) = exp(0.5928 (log TRM - 1.8117) + 0.6450 (stage - 0.3827) + 0.6673 (C4 - 0.4198) - 0.8596 (CAP - 0.8642)), where lambda i(t)/lambda o(t) is the risk of dying for a particular patient compared with the average risk of the entire group; log TRM is the log of the volume of the total residual mass in cm3 plus 1.0; stage = 0 if stage III, 1 if stage IV; C4 = 0 if cytologic grade is 1, 2, or 3 and 1 if grade 4; CAP = 0 if treatment is cyclophosphamide and 1 if CAP. Median survival times of patients with relative risk greater than 1 and less than 1 are 43 and 19 months respectively. If this model is confirmed in a prospective study, then it could be used to assign risk and assess treatment options for similar patients at diagnosis.

UI MeSH Term Description Entries
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009367 Neoplasm Staging Methods which attempt to express in replicable terms the extent of the neoplasm in the patient. Cancer Staging,Staging, Neoplasm,Tumor Staging,TNM Classification,TNM Staging,TNM Staging System,Classification, TNM,Classifications, TNM,Staging System, TNM,Staging Systems, TNM,Staging, Cancer,Staging, TNM,Staging, Tumor,System, TNM Staging,Systems, TNM Staging,TNM Classifications,TNM Staging Systems
D010051 Ovarian Neoplasms Tumors or cancer of the OVARY. These neoplasms can be benign or malignant. They are classified according to the tissue of origin, such as the surface EPITHELIUM, the stromal endocrine cells, and the totipotent GERM CELLS. Cancer of Ovary,Ovarian Cancer,Cancer of the Ovary,Neoplasms, Ovarian,Ovary Cancer,Ovary Neoplasms,Cancer, Ovarian,Cancer, Ovary,Cancers, Ovarian,Cancers, Ovary,Neoplasm, Ovarian,Neoplasm, Ovary,Neoplasms, Ovary,Ovarian Cancers,Ovarian Neoplasm,Ovary Cancers,Ovary Neoplasm
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
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D005260 Female Females
D005500 Follow-Up Studies Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease. Followup Studies,Follow Up Studies,Follow-Up Study,Followup Study,Studies, Follow-Up,Studies, Followup,Study, Follow-Up,Study, Followup
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000367 Age Factors Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time. Age Reporting,Age Factor,Factor, Age,Factors, Age
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly

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