  Building on Yu and Kumbier's PCS framework and for randomized experiments, we
introduce a novel methodology for Stable Discovery of Interpretable Subgroups
via Calibration (StaDISC), with large heterogeneous treatment effects. StaDISC
was developed during our re-analysis of the 1999-2000 VIGOR study, an 8076
patient randomized controlled trial (RCT), that compared the risk of adverse
events from a then newly approved drug, Rofecoxib (Vioxx), to that from an
older drug Naproxen. Vioxx was found to, on average and in comparison to
Naproxen, reduce the risk of gastrointestinal (GI) events but increase the risk
of thrombotic cardiovascular (CVT) events. Applying StaDISC, we fit 18 popular
conditional average treatment effect (CATE) estimators for both outcomes and
use calibration to demonstrate their poor global performance. However, they are
locally well-calibrated and stable, enabling the identification of patient
groups with larger than (estimated) average treatment effects. In fact, StaDISC
discovers three clinically interpretable subgroups each for the GI outcome
(totaling 29.4% of the study size) and the CVT outcome (totaling 11.0%).
Complementary analyses of the found subgroups using the 2001-2004 APPROVe
study, a separate independently conducted RCT with 2587 patients, provides
further supporting evidence for the promise of StaDISC.
