No abstract

Background Classical phase 1 dose-finding designs based on a single toxicity endpoint to assess the maximum tolerated dose were initially developed in the context of cytotoxic drugs. With the emergence of molecular targeted agents and immunotherapies, the concept of optimal biological dose (OBD) was subsequently introduced to account for efficacy in addition to toxicity. The objective was therefore to provide an overview of published phase 1 cancer clinical trials relying on the concept of OBD. Methods We performed a systematic review through a computerized search of the MEDLINE database to identify early phase cancer clinical trials that relied on OBD. Relevant publications were selected based on a two-step process by two independent readers. Relevant information (phase, type of therapeutic agents, objectives, endpoints and dose-finding design) were collected. Results We retrieved 37 articles. OBD was clearly mentioned as a trial objective (primary or secondary) for 22 articles and was traditionally defined as the smallest dose maximizing an efficacy criterion such as biological target: biological response, immune cells count for immunotherapies, or biological cell count for targeted therapies. Most trials considered a binary toxicity endpoint defined in terms of the proportion of patients who experienced a dose-limiting toxicity. Only two articles relied on an adaptive dose escalation design. Conclusions In practice, OBD should be a primary objective for the assessment of the recommended phase 2 dose (RP2D) for a targeted therapy or immunotherapy phase I cancer trial. Dose escalation designs have to be adapted accordingly to account for both efficacy and toxicity.

No abstract

Background Soft‐tissue sarcomas (STSs) are a group of rare cancers that can occur at any age. Prognostic outcomes of patients with STS are usually established at the time of the patient's initial disease presentation. Conditional survival affords a dynamic prediction of prognosis for patients surviving a given period after diagnosis. Estimates of conditional survival can provide crucial prognostic information for patients and caregivers, guide subsequent cancer follow‐up schedules, and impact decisions regarding management. This study aims to estimate conditional survival and prognostic factors in patients with STS according to age at diagnosis (≤75 years and ≥75 years). Subjects, Materials, and Methods A total of 6,043 patients with nonmetastatic STS at first diagnosis who underwent complete surgical resection (R0 or R1) were assessed. Cox proportional hazards regression was used to establish prognostic factors of conditional metastasis‐free survival and overall survival at 1, 2, and 5 years after diagnosis. Results Elderly patients have more adverse prognostic features at presentation and tend to receive less aggressive treatment than do younger patients. However, at baseline as well as at each conditional survival time point, the 5‐year estimated probability of metastatic relapse decreases in both young and elderly patients and is almost identical in both groups at 2 years and 5 years after initial diagnosis. Prognostic factors for metastatic relapse and death change as patient survival time increases in both young and elderly patients. Grade, the strongest prognostic factor for metastatic relapse and death at baseline, is no longer predictive of metastatic relapse in patients surviving 5 years after initial diagnosis. Leiomyosarcoma is the histological subtype associated with the highest risk of metastatic relapse and death in young patients surviving 5 years after initial diagnosis. The positive impact on the outcome of peri‐operative treatments tends to decrease and disappears in patients surviving 5 years after initial diagnosis. Conclusion Conditional survival estimates show clinically relevant variations according to time since first diagnosis in both young and elderly patients with STS. These results can help STS survivors adjust their view of the future and STS care providers plan patient follow‐up. Implications for Practice For patients with sarcoma who are followed up years after being treated for their disease, a common scenario is for the patient and caregivers to ask practitioners what the longer‐term prognosis may be. The question posed to practitioners may be, “Doc, am I now cured? It's been 5 years since we finished treatment.” Survival probability changes for patients who survive a given period of time after diagnosis, and their prognosis is more accurately described using conditional survival. By analyzing more than 6,000 sarcoma patients, an overall improvement was found in the risk of relapse as patients conditionally survive. Prognostic factors for metastatic relapse and death cha...