Background: Immune‐related pneumonitis is a clinically relevant and potentially life‐threatening adverse event. We performed a systematic review and network meta‐analysis to compare the risk of immune‐related pneumonitis among different PD1/PD‐L1 inhibitor‐related therapeutic regimens.Methods: Randomized controlled trials with PD1/PD‐L1 inhibitors were identified through comprehensive searches of multiple databases. Both published and unpublished data were extracted. Bayesian NMA was performed using random‐effects models. All‐grade (Grade 1‐5) and high‐grade (Grade 3‐5) immune‐related pneumonitis were estimated using odds ratios (ORs).Results: A total of 25 studies involving 16 005 patients were included. Compared with chemotherapy, the ORs of immune‐related all‐grade and high‐grade pneumonitis were significant for nivolumab (all‐grade: OR = 6.29, 95% CrI: 2.67‐16.75; high‐grade: OR = 5.95, 95% CrI: 2.35‐17.29), pembrolizumab (all‐grade: OR = 5.78, 95% CrI: 2.79‐13.24; high‐grade: OR = 5.33, 95% CrI: 2.49‐12.97), and nivolumab plus ipilimumab therapy (all‐grade: OR = 14.82, 95% CrI: 5.48‐47.97; high‐grade: OR = 15.26, 95% CrI: 5.05‐55.52). Compared with nivolumab, nivolumab plus ipilimumab therapy was associated with an increased risk of all‐grade pneumonitis (OR = 2.34, 95% CrI: 1.07‐5.77). Nivolumab plus ipilimumab therapy had the highest risk of both all‐grade and high‐grade pneumonitis among PD1/PD‐L1 inhibitor‐related therapeutic regimens.Conclusions: This study demonstrates that compared with chemotherapy, PD‐1 inhibitor may result in a higher risk of immune‐related pneumonitis. Nivolumab plus ipilimumab therapy had the highest pneumonitis risk. These findings could be taken into account by the physicians in decision making.

To characterize the indications approved by the US Food and Drug Administration (FDA) on the basis of early phase clinical trials (EPCTs) and compared with that of phase three randomized controlled trials. We collected the publicly available FDA documents of targeted anticancer drugs approved between January 2012 and December 2021. We identified 95 targeted anticancer drugs with 188 indications approved by the FDA. One hundred and twelve (59.6%) indications were approved on the basis of EPCTs, with a significant increase of 22.2% per year. Of 112 EPCTs, 32 (28.6%) were dose-expansion cohort trials and 75 (67.0%) were single-arm phase 2 trials, respectively, with a significant increase of 29.7% and 18.7% per year. Compared with indications approved on the basis of phase three randomized controlled trials, the indications approved on the basis of EPCTs had significantly higher odds in receiving accelerated approval and lower odds in the number of entered patients of pivotal trials. Dose-expansion cohort trials and single-arm phase 2 trials played a critical role in EPCTs. EPCT was a major trial type in providing evidences for the FDA approvals of targeted anticancer drugs.

Background: The surge in artificial intelligence (AI) interventions in primary care trials lacks a study on reporting quality. Objective: This study aimed to systematically evaluate the reporting quality of both published randomized controlled trials (RCTs) and protocols for RCTs that investigated AI interventions in primary care. Methods: PubMed, Embase, Cochrane Library, MEDLINE, Web of Science, and CINAHL databases were searched for RCTs and protocols on AI interventions in primary care until November 2024. Eligible studies were published RCTs or full protocols for RCTs exploring AI interventions in primary care. The reporting quality was assessed using CONSORT-AI (Consolidated Standards of Reporting Trials–Artificial Intelligence) and SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials–Artificial Intelligence) checklists, focusing on AI intervention–related items. Results: A total of 11,711 records were identified. In total, 19 published RCTs and 21 RCT protocols for 35 trials were included. The overall proportion of adequately reported items was 65% (172/266; 95% CI 59%-70%) and 68% (214/315; 95% CI 62%-73%) for RCTs and protocols, respectively. The percentage of RCTs and protocols that reported a specific item ranged from 11% (2/19) to 100% (19/19) and from 10% (2/21) to 100% (21/21), respectively. The reporting of both RCTs and protocols exhibited similar characteristics and trends. They both lack transparency and completeness, which can be summarized in three aspects: without providing adequate information regarding the input data, without mentioning the methods for identifying and analyzing performance errors, and without stating whether and how the AI intervention and its code can be accessed. Conclusions: The reporting quality could be improved in both RCTs and protocols. This study helps promote the transparent and complete reporting of trials with AI interventions in primary care.

Early-phase clinical trials (EPCTs) have been increasingly adopted as the pivotal trial to support US Food and Drug Administration (FDA) approval of novel anticancer drugs. Among EPCT designs, dose-escalation and -expansion cohort (DEEC) substantially reduces the time and resources that are required in the traditional three-phase paradigm. DEEC facilitates expedited approvals of investigational drugs, particularly those targeting novel mechanisms, helping to address the pressing needs of patients with cancer. From 2012 to 2023, DEECs provided pivotal trial evidence that supported the FDA approval for 46 indications across 36 targeted anticancer drugs. Dose escalation uses 3 + 3, Bayesian optimal interval design, or continual reassessment method to explore the optimal dose level, whereas expansion cohorts directly incorporate dose-escalation cohort at the recommended phase II dose level. Expansion cohorts adopt flexible designs such as basket, umbrella, and platform trials. In addition, each expansion cohort in DEEC often uses adaptive approaches, such as Simon's two-stage design. To avoid the bias of end point assessment, conducting DEEC trials requires end point adjudication, often by an independent review committee. The design, conduct, and analysis of DEEC trials each have distinct characteristics. However, these characteristics were often overlooked in DEEC reporting. We reviewed the structural domains and items in trial design and conduct and discussed the strengths and limitations of DEEC studies, aiming to enhance the utilization of this trial design to generate higher-quality clinical evidence and ultimately contribute to better outcomes for patients with cancer.

Background: Hundreds of cancer drugs are approved globally based on surrogate endpoint response rate (RR). However, the characteristics of RR‐based approvals remain unknown.Methods: In this retrospective study, all cancer drug‐indication pairs approved based on RR in the United States and China up to December 2023 were analyzed.Results: A total of 249 RR‐supported drug‐indication pairs were identified in the United States and 98 in China. In the United States, 98 of the 249 (39.4%) indications were granted regular approval (RA), whereas in China, only 21 of 98 (21.4%) approvals followed this regulatory pathway, with the remainder receiving accelerated approval (AA). The conversion rate from AA to RA was significantly lower in China compared to the United States (13.3% vs. 28.1%, p < 0.001). The proportion of AA withdrawals was significantly lower in China compared to the United States (1.0% vs. 10.4%, p < 0.001). Among all indications, the median RR in China was 60.9% (IQR, 35.8%–75.0%), which was significantly higher than the 45.0% (IQR, 29.0%–61.0%) in the United States (p < 0.001). In China, 18 of the 98 (18.4%) had an RR less than 30%. In contrast, in the United States, 26.9% of the 249 had an RR less than 30%.Conclusions: Compared to the United States, RR‐supported approvals in China are characterized by higher RR values and a stricter RA pathway. Regulatory authorities in both countries may need to consider both the quantity and quality during cancer drug development based on surrogate endpoints.