Potential harm caused by physicians a-priori beliefs in the clinical effectiveness of hydroxychloroquine and its impact on clinical and economic outcome – A simulation approach

Background Despite growing controversies around Hydroxychloroquine's effectiveness, the drug is still widely prescribed by clinicians to treat COVID19 patients. Therapeutic judgment under uncertainty and imperfect information may be influenced by personal preference, whereby individuals, to confirm a-priori beliefs, may propose drugs without knowing the clinical benefit. To estimate this disconnect between available evidence and prescribing behavior, we created a Bayesian model analyzing a-priori optimistic belief of physicians in Hydroxychloroquine's effectiveness. Methodology: We created a Bayesian model to simulate the impact of different a-priori beliefs related to Hydroxychloroquine's effectiveness on clinical and economic outcome. Results: Our hypothetical results indicate no significant difference in treatment effect (combined survival benefit and harm) up to a presumed drug's effectiveness level of 20%, with younger individuals being negatively affected by the treatment (RR 0.82, 0.55–1.2; (0.95 (1.1) % expected adverse events versus 0.05 (0.98) % expected death prevented). Simulated cost data indicate overall hospital cost (medicine, hospital stay, complication) of 18.361,41€ per hospitalized patient receiving Hydroxychloroquine treatment. Conclusion: Off-label use of Hydroxychloroquine needs a rational, objective and datadriven evaluation, as personal preferences may be flawed and cause harm to patients and to society.
Highlights • Hydroxychloroquine has been widely used as an off-label drug during the COVID-19 pandemic despite accumulating evidence showing limited clinical effectiveness • Subjective preference during emergencies may skew clinical judgment about benefit versus harm in prescribing Hydroxychloroquine • We have quantified the internal belief of “optimistic believers in the effectiveness of the drug” to be around or above 20% • Increasing awareness of personal bias may reduce waste and improve the quality of informed prescribing