PURPOSE: To determine how modelled maximum tumor control rates, achievable without exceeding mucositis tolerance (tcp(max-early)) vary with schedule duration for head and neck squamous cell carcinoma (HNSCC). METHODS AND MATERIALS: Using maximum-likelihood techniques, we have fitted a range of tcp models to two HNSCC datasets (Withers' and British Institute of Radiology [BIR]), characterizing the dependence of tcp on duration and equivalent dose in 2 Gy fractions (EQD(2)). Models likely to best describe future data have been selected using the Akaike information criterion (AIC) and its quasi-AIC extension to overdispersed data. Setting EQD(2)s in the selected tcp models to levels just tolerable for mucositis, we have plotted tcp(max-early) against schedule duration. RESULTS: While BIR dataset tcp fits describe dose levels isoeffective for tumor control as rising significantly with schedule protraction, indicative of accelerated tumor repopulation, repopulation terms in fits to Withers' dataset do not reach significance after accounting for overdispersion of the data. The tcp(max-early) curves calculated from tcp fits to the overall Withers' and BIR datasets rise by 8% and 0-4%, respectively, between 20 and 50 days duration; likewise, tcp(max-early) curves calculated for stage-specific cohorts also generally rise slowly with increasing duration. However none of the increases in tcp(max-early) calculated from the overall or stage-specific fits reach significance. CONCLUSIONS: Local control rates modeled for treatments which lie just within mucosal tolerance rise slowly but insignificantly with increasing schedule length. This finding suggests that whereas useful gains may be made by accelerating unnecessarily slow schedules until they approach early reaction tolerance, little is achieved by shortening schedules further while reducing doses to remain within mucosal tolerance, an approach that may slightly worsen outcomes.
PURPOSE: To determine how modelled maximum tumor control rates, achievable without exceeding mucositis tolerance (tcp(max-early)) vary with schedule duration for head and neck squamous cell carcinoma (HNSCC). METHODS AND MATERIALS: Using maximum-likelihood techniques, we have fitted a range of tcp models to two HNSCC datasets (Withers' and British Institute of Radiology [BIR]), characterizing the dependence of tcp on duration and equivalent dose in 2 Gy fractions (EQD(2)). Models likely to best describe future data have been selected using the Akaike information criterion (AIC) and its quasi-AIC extension to overdispersed data. Setting EQD(2)s in the selected tcp models to levels just tolerable for mucositis, we have plotted tcp(max-early) against schedule duration. RESULTS: While BIR dataset tcp fits describe dose levels isoeffective for tumor control as rising significantly with schedule protraction, indicative of accelerated tumor repopulation, repopulation terms in fits to Withers' dataset do not reach significance after accounting for overdispersion of the data. The tcp(max-early) curves calculated from tcp fits to the overall Withers' and BIR datasets rise by 8% and 0-4%, respectively, between 20 and 50 days duration; likewise, tcp(max-early) curves calculated for stage-specific cohorts also generally rise slowly with increasing duration. However none of the increases in tcp(max-early) calculated from the overall or stage-specific fits reach significance. CONCLUSIONS: Local control rates modeled for treatments which lie just within mucosal tolerance rise slowly but insignificantly with increasing schedule length. This finding suggests that whereas useful gains may be made by accelerating unnecessarily slow schedules until they approach early reaction tolerance, little is achieved by shortening schedules further while reducing doses to remain within mucosal tolerance, an approach that may slightly worsen outcomes.