M. Guillaume Wientjes

Isobologram and combination index (CI) analyses are the two most popular methods for evaluating drug interactions in combination cancer chemotherapy. As the commonly used CI-based software program uses linear regression, our first objective was to evaluate the effects of logarithmic data transformation on data analysis and conclusions. Monte-Carlo simulations were conducted with experimentally relevant parameter values to generate error-containing effect or concentration-effect data of single agents and combinations. The simulated data were then analyzed with linear and nonlinear regression. The results showed that data transformation reduced the accuracy and precision of the regression-derived IC(50), curve shape parameter and CI values. Furthermore, as neither isobologram nor CI analyses provide output of concentration-effect curves for investigator evaluation, our second objective was to develop a method and the associated computer program/algorithm to (a) normalize drug concentrations in IC(50) equivalents and thereby enable simultaneous presentation of the curves for single agents and combinations in a single plot for visual inspection of potential curve shifts, (b) analyze concentration-effect data with nonlinear regression, and (c) use the curve shift analysis simultaneously with isobologram and CI analyses. The applicability of this method was shown with experimentally obtained data for single agent doxorubicin and suramin and their combinations in cultured tumor cells. In summary, this method, by incorporating nonlinear regression and curve shift analysis, although retaining the attractive features of isobologram and CI analyses, reduced the potential errors introduced by logarithmic data transformation, enabled visual inspection of data variability and goodness of fit of regression analysis, and simultaneously provided information on the extent of drug interaction at different combination ratios/concentrations and at different effect levels.

BACKGROUND: Intravesical chemotherapy (i.e., placement of the drug directly in the bladder) with mitomycin C is beneficial for patients with superficial bladder cancer who are at high risk of recurrence, but standard therapy is empirically based and patient response rates have been variable, in part because of inadequate drug delivery. We carried out a prospective, two-arm, randomized, multi-institutional phase III trial to test whether enhancing the drug's concentration in urine would improve its efficacy. METHODS: Patients with histologically proven transitional cell carcinoma and at high risk for recurrence were eligible for the trial. Patients in the optimized-treatment arm (n = 119) received a 40-mg dose of mitomycin C, pharmacokinetic manipulations to increase drug concentration by decreasing urine volume, and urine alkalinization to stabilize the drug. Patients in the standard-treatment arm (n = 111) received a 20-mg dose without pharmacokinetic manipulations or urine alkalinization. Both treatments were given weekly for 6 weeks. Primary endpoints were recurrence and time to recurrence. Treatment outcome was examined by use of Kaplan-Meier analysis with log-rank tests. Statistical tests were two-sided. RESULTS: Patients in the two arms did not differ in demographics or history of intravesical therapy. Dysuria occurred more frequently in the optimized arm but did not lead to more frequent treatment termination. In an intent-to-treat analysis, patients in the optimized arm showed a longer median time to recurrence (29.1 months; 95% confidence interval [CI] = 14.0 to 44.2 months) and a greater recurrence-free fraction (41.0%; 95% CI = 30.9% to 51.1%) at 5 years than patients in the standard arm (11.8 months; 95% CI = 7.2 to 16.4 months) and 24.6% (95% CI = 14.9% to 34.3%) (P =.005, log-rank test for time to recurrence). Improvements were found in all risk groups defined by tumor stage, grade, focality, and recurrence. CONCLUSIONS: This study identified a pharmacologically optimized intravesical mitomycin C treatment with statistically significantly enhanced efficacy.