Medline ® Abstracts for References 68,69
of 'Medical treatment for relapsed epithelial ovarian, fallopian tubal, or peritoneal cancer: Platinum-sensitive disease'
Progression-free interval in ovarian cancer and predictive value of an ex vivo chemoresponse assay.
Gallion H, Christopherson WA, Coleman RL, DeMars L, Herzog T, Hosford S, Schellhas H, Wells A, Sevin BU
Int J Gynecol Cancer. 2006;16(1):194.
The study objective was to determine the effectiveness of a phenotypic chemoresponse assay in predicting response to chemotherapy measured by progression-free interval (PFI) in a retrospective series of ovarian cancer patients whose tumor specimens had been tested with the ChemoFx assay. A statistically significant correlation between assay prediction of response and PFI was observed in 256 cases with an exact or partial match between drug(s) assayed and received. In 135 cases with an exact match, the hazard ratio for progression of the resistant group was 2.9 (confidence interval [CI]: 1.4-6.3; P<0.01) compared to the sensitive group and 1.7 (CI: 1.2-2.5) for the intermediate compared to the sensitive group. The median PFI for patients treated with drugs assayed as resistant was 9 months, 14 months for those with drugs assayed as intermediately sensitive, and PFI had not been achieved for those with drugs assayed as sensitive. These data indicate that the ChemoFx assay is predictive of PFI in ovarian cancer. As the majority of ovarian cancers display different degrees of response to different chemotherapy agents ex vivo, the incorporation of assay information into treatment selection has the potential to improve clinical outcomes in ovarian cancer patients.
Precision Therapeutics Inc., 2516 Jane Street, Pittsburgh, PA 15203, USA. firstname.lastname@example.org
Highly specific prediction of antineoplastic drug resistance with an in vitro assay using suprapharmacologic drug exposures.
Kern DH, Weisenthal LM
J Natl Cancer Inst. 1990;82(7):582.
Bayes' theorem has been used to describe the relationship between the accuracy of a predictive test (posttest probability) and the overall incidence of what is being tested (pretest probability). Bayes' theorem indicates that laboratory assays will be accurate in the prediction of clinical drug resistance in tumors with high overall response rates (e.g., previously untreated breast cancer) only when the assays are extremely (greater than 98%) specific for drug resistance. We developed a highly specific drug-resistance assay in which human tumor colonies were cultured in soft agar and drugs were tested at high concentrations for long exposure times. Coefficients for concentration x time exceeded those reported in contemporaneous studies by about 100-fold. We reviewed 450 correlations between assay results and clinical response over an 8-year period. Results were analyzed by subsets, including different tumor histologies, single agents, and drug combinations. Extreme drug resistance (an assay result greater than or equal to SD below the median) was identified with greater than 99% specificity. Only one of 127 patients with tumors showing extreme drug resistance responded to chemotherapy. This negligible posttest probability of response was independent of pretest (expected) probability of response. Once this population of patients with tumors showing extreme drug resistance had been identified, posttest response probabilities for the remaining cohorts ofpatients varied according to both assay results and pretest response probabilities, precisely according to predictions based on Bayes' theorem. This finding allowed the construction of a nomogram for determining assay-predicted probability of response.
Oncotech, Inc., Irvine, CA 92714.