Fungal infection-related mortality versus total mortality as an outcome in trials of antifungal agents.

BACKGROUND: Disease specific mortality is often used as outcome rather than total mortality in clinical trials. This approach assumes that the classification of cause of death is unbiased. We explored whether use of fungal infection-related mortality as outcome rather than total mortality leads to bias in trials of antifungal agents in cancer patients. METHODS: As an estimate of bias we used relative risk of death in those patients the authors considered had not died from fungal infection. Our sample consisted of 69 trials included in four systematic reviews of prophylactic or empirical antifungal treatment in patients with cancer and neutropenia we have published previously. RESULTS: Thirty trials met the inclusion criteria. The trials comprised 6130 patients and 869 deaths, 220 (25%) of which were ascribed to fungal infection. The relative risk of death was 0.85 (95% CI 0.75-0.96) for total mortality, 0.57 (95% CI 0.44-0.74) for fungal mortality, and 0.95 (95% CI 0.82-1.09) for mortality among those who did not die from fungal infection. CONCLUSION: We could not support the hypothesis that use of disease specific mortality introduces bias in antifungal trials on cancer patients as our estimate of the relative risk for mortality in those who survived the fungal infection was not increased. We conclude that it seems to be reliable to use fungal mortality as the primary outcome in trials of antifungal agents. Data on total mortality should be reported as well, however, to guard against the possible introduction of harmful treatments.

Recurrences after intensity modulated radiotherapy for head and neck squamous cell carcinoma more likely to originate from regions with high baseline [18F]-FDG uptake.

BACKGROUND AND PURPOSE: To analyze the recurrence pattern in relation to target volumes and (18)F-fluorodeoxyglucose (FDG) uptake on positron emission tomography in head and neck squamous cell carcinoma (HNSCC) patients treated with definitive chemoradiation. MATERIAL AND METHODS: 520 patients received radiotherapy for HNSCC from 2005 to 2009. Among 100 patients achieving complete clinical response and a later recurrence, 39 patients with 48 loco-regional failures had a recurrence CT scan before any salvage therapy. The estimated point of origin of each recurrence was transferred to the planning CT by deformable image co-registration. The recurrence position was then related to the delineated target volumes and iso-SUV-contours relative to the maximum standard uptake value (SUV). We defined the recurrence density as the total number of recurrences in a sub-volume divided by the sum of that volume for all patients. RESULTS: 54% (95% CI 37-69%) of recurrences originated inside the FDG-positive volume and 96% (95% CI 86-99%) in the high dose region. Recurrence density was significantly higher in the central target volumes (P<0.0001) and increased with increasing FDG avidity (P=0.036). CONCLUSIONS: The detailed pattern-of-failure data analysis suggests that most recurrences occur in the FDG PET positive areas or the solid tumor.

Failure-probability driven dose painting.

PURPOSE: To demonstrate a data-driven dose-painting strategy based on the spatial distribution of recurrences in previously treated patients. The result is a quantitative way to define a dose prescription function, optimizing the predicted local control at constant treatment intensity. A dose planning study using the optimized dose prescription in 20 patients is performed. METHODS: Patients treated at our center have five tumor subvolumes from the center of the tumor (PET positive volume) and out delineated. The spatial distribution of 48 failures in patients with complete clinical response after (chemo)radiation is used to derive a model for tumor control probability (TCP). The total TCP is fixed to the clinically observed 70% actuarial TCP at five years. Additionally, the authors match the distribution of failures between the five subvolumes to the observed distribution. The steepness of the dose-response is extracted from the literature and the authors assume 30% and 20% risk of subclinical involvement in the elective volumes. The result is a five-compartment dose response model matching the observed distribution of failures. The model is used to optimize the distribution of dose in individual patients, while keeping the treatment intensity constant and the maximum prescribed dose below 85 Gy. RESULTS: The vast majority of failures occur centrally despite the small volumes of the central regions. Thus, optimizing the dose prescription yields higher doses to the central target volumes and lower doses to the elective volumes. The dose planning study shows that the modified prescription is clinically feasible. The optimized TCP is 89% (range: 82%-91%) as compared to the observed TCP of 70%. CONCLUSIONS: The observed distribution of locoregional failures was used to derive an objective, data-driven dose prescription function. The optimized dose is predicted to result in a substantial increase in local control without increasing the predicted risk of toxicity.