A critical reassessment of second-look laparotomy in epithelial ovarian carcinoma. 1986

D S Miller, and S C Ballon, and N N Teng, and D B Seifer, and O M Soriero

Eighty-eight women with epithelial ovarian carcinoma, treated by first-line chemotherapy, achieved a complete clinical response and underwent second-look laparotomy to assess the true pathologic status of their disease. Persistent tumor was found in 50 patients (57%). Thirty-two of these (36%) had obvious gross tumor, whereas, 16 (18%) had microscopic disease. Thirty-eight patients (43%) had no pathologic evidence of persistent ovarian carcinoma. With a follow-up of 6 to 60 months, 30 of these patients (79%) remain without evidence of recurrence. Multivariate logistic regression analysis revealed three covariates that were independently significant in predicting continued disease-free status. These included: the greatest diameter of the largest residual tumor left at the primary operation; histologic features of the tumor; and the diameter of the largest tumor aggregate found at initial operation. A mathematical model based on the most significant covariates was designed to assess the relative risk of any patient having persistent tumor at second-look laparotomy. A comparison of the predicted to actual outcome revealed a sensitivity of the model of 88%, a specificity of 71%, and an accuracy of 77%. Second-look laparotomy represents the basis on which potentially curative second-line salvage therapy can be initiated. With an increasing period of follow-up and with greater numbers of patients, it can potentially document a complete pathologic response to first-line therapy administered with curative intent, and identify patients for additional, adjunctive therapy, who are at risk of recurrence.

UI MeSH Term Description Entries
D007813 Laparotomy Incision into the side of the abdomen between the ribs and pelvis. Minilaparotomy,Laparotomies,Minilaparotomies
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009364 Neoplasm Recurrence, Local The local recurrence of a neoplasm following treatment. It arises from microscopic cells of the original neoplasm that have escaped therapeutic intervention and later become clinically visible at the original site. Local Neoplasm Recurrence,Local Neoplasm Recurrences,Locoregional Neoplasm Recurrence,Neoplasm Recurrence, Locoregional,Neoplasm Recurrences, Local,Recurrence, Local Neoplasm,Recurrence, Locoregional Neoplasm,Recurrences, Local Neoplasm,Locoregional Neoplasm Recurrences,Neoplasm Recurrences, Locoregional,Recurrences, Locoregional Neoplasm
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
D002277 Carcinoma A malignant neoplasm made up of epithelial cells tending to infiltrate the surrounding tissues and give rise to metastases. It is a histological type of neoplasm and not a synonym for "cancer." Carcinoma, Anaplastic,Carcinoma, Spindle-Cell,Carcinoma, Undifferentiated,Carcinomatosis,Epithelial Neoplasms, Malignant,Epithelioma,Epithelial Tumors, Malignant,Malignant Epithelial Neoplasms,Neoplasms, Malignant Epithelial,Anaplastic Carcinoma,Anaplastic Carcinomas,Carcinoma, Spindle Cell,Carcinomas,Carcinomatoses,Epithelial Neoplasm, Malignant,Epithelial Tumor, Malignant,Epitheliomas,Malignant Epithelial Neoplasm,Malignant Epithelial Tumor,Malignant Epithelial Tumors,Neoplasm, Malignant Epithelial,Spindle-Cell Carcinoma,Spindle-Cell Carcinomas,Tumor, Malignant Epithelial,Undifferentiated Carcinoma,Undifferentiated Carcinomas
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man

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