{'fraction_non_alphanumeric': 0.012549537648612946, 'fraction_numerical': 0.0, 'mean_word_length': 5.209016393442623, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
BLAST: Bayesian latent subgroup design for basket trials accounting for patient heterogeneity

The basket trial refers to a new type of phase II cancer trial that evaluates the therapeutic effect of a targeted agent simultaneously in patients with different types of cancer that involve the same genetic or molecular aberration. Although patients who are enrolled in the basket trial have the same molecular aberration, it is common for the targeted agent to be effective for patients with some types of cancer, but not others. We propose a Bayesian latent subgroup trial (BLAST) design to accommodate such treatment heterogeneity across cancer types. We assume that a cancer type may belong to the sensitive subgroup, which is responsive to the treatment, or the insensitive subgroup, which is not responsive to the treatment. Conditionally on the latent subgroup membership of the cancer type, we jointly model the binary treatment response and the longitudinal biomarker measurement that represents the biological activity of the targeted agent. The BLAST design makes the interim go–no‐go treatment decision in a group sequential fashion for each cancer type on the basis of accumulating data. The simulation study shows that the BLAST design outperforms existing trial designs. It yields high power to detect the treatment effect for sensitive cancer types that are responsive to the treatment and maintains a reasonable type I error rate for insensitive cancer types that are not responsive to the treatment.