ABSTRACT
Delayed outcome is common in phase I oncology clinical trials. It causes logistic difficulty, wastes resources, and prolongs the trial duration. This article investigates this issue and proposes the time-to-event 3 + 3 (T3 + 3) design, which utilizes the actual follow-up time for at-risk patients with pending toxicity outcomes. The T3 + 3 design allows continuous accrual without unnecessary trial suspension and is costless and implementable with pretabulated dose decision rules. Besides, the T3 + 3 design uses the isotonic regression to estimate the toxicity rates across dose levels and therefore can accommodate for any targeted toxicity rate for maximum tolerated dose (MTD). It dramatically facilitates the trial preparation and conduct without intensive computation and statistical consultation. The extension to other algorithm-based phase I dose-finding designs (e.g., i3 + 3 design) is also studied. Comprehensive computer simulation studies are conducted to investigate the performance of the T3 + 3 design under various dose-toxicity scenarios. The results confirm that the T3 + 3 design substantially shortens the trial duration compared with the conventional 3 + 3 design and yields much higher accuracy in MTD identification than the rolling six design. In summary, the T3 + 3 design addresses the delayed outcome issue while keeping the desirable features of the 3 + 3 design, such as simplicity, transparency, and costless implementation. It has great potential to accelerate early-phase drug development.
ABSTRACT
Background: Increasing epidemiological evidence supported that chronic inflammatory factors might be involved in the carcinogenesis and progression of various cancers. The present study tried to investigate the prognostic value of perioperative C-reactive protein (CRP) in prognosis of patients with epithelial ovarian carcinoma (EOC) from a tertiary university teaching hospital. Methods: The cutoff value of CRP was calculated according to receiver operating characteristic (ROC) curve. Variables were compared using Chi-square test. Progress-free survival (PFS) and overall survival (OS) time were assessed by Kaplan-Meier (KM) survival analysis and Log rank test based on serum CRP level. Univariate and multivariate Cox regression analyses were applied for assessing the relationship between clinicopathological parameters and survival. Results: Higher perioperative CRP levels (preoperative ≥5.15 mg/L and postoperative ≥72.45 mg/L) were significantly associated with serous tumor, high-grade, advanced stage, elevated preoperative CA125, suboptimal surgery, chemotherapy resistance, recurrence and death in EOC (P < 0.01). KM analysis suggested patients with elevated preoperative, postoperative and perioperative CRP had shorter survival (P < 0.01). Elevated perioperative CRP was an independent risk factor for PFS (HR 1.510, 95% CI 1.124-2.028; P = 0.006) and OS (HR 1.580, 95% CI 1.109-2.251; P = 0.011). Similar results were obtained for elevated preoperative CRP. Subgroup analysis further suggested that elevated perioperative CRP was also an independent risk factor for prognosis in advanced stage and serous EOC. Conclusion: Elevated perioperative CRP was an independent risk factor for poorer prognosis of EOC, particularly in advanced stage and serous patients.
ABSTRACT
It is not uncommon that clinical studies of the same intervention contradicted with each other, e.g., one study produced positive results, while the other produced negative results. Ioanndis (2005a) found that among 49 highly-cited original clinical research studies, published in New England Journal of Medicine, Journal of the American Medical Association, Lancet or in a high-impact medical specialty journal, 32% of them were contradicted in subsequent large-scale studies, or were shown to have potentially overestimated the efficacy of the experimental intervention. This finding is disturbing and of serious concern given the widespread impact of these highly-cited studies and the rigorous standards used to design and conduct the studies. We perform Bayesian analysis of these highly-cited clinical studies based on Bayesian factor. We identified one cause of the issue: p values strongly overstated the experimental evidence. For the highly-cited studies, when the p value was 0.05, there was a 74.4% percentage chance that the null hypothesis was true. The use of a p value of 0.05 as the criterion for significance caused many researchers to mistakenly draw conclusions of positive findings, which were then contradicted by subsequent large-scale studies.
