Consolidated Health Economic Evaluation Reporting Standards for Interventions that use Artificial Intelligence (CHEERS-AI).

OBJECTIVES: Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed CHEERS-AI to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner. METHODS: Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalise outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective. RESULTS: A total of 58 participants responded to survey round 1, 42 and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported. CONCLUSIONS: CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions.

Immune checkpoint inhibitors of the PD-1/PD-L1-axis in non-small cell lung cancer: promise, controversies and ambiguities in the novel treatment paradigm.

Immune checkpoint inhibitors (ICIs) have received much attention not least for melanoma since the award of the Nobel prize in 2018. Here, we review the current state of knowledge about the use of these monoclonal antibodies (mAbs) in non-small cell lung cancer (NSCLC). These drugs have generally been conditionally approved on limited early data and there are few long-term follow-up data from randomized clinical trials. The effect observed for NSCLC thus far is, on average, moderately better than that obtained with chemotherapy. Severe side-effects are more common than might have been expected. The drugs themselves are expensive and are associated with time-consuming histopathologic testing even though the predictive value of these tests can be discussed. In addition, monitoring for side-effects involves increased workload and budgetary expense for clinical chemistry laboratories. Here, we review and summarize the current knowledge, controversies and ambiguities of ICIs for the treatment of NSCLC.