Rishi J Desai, Robert J Glynn, Scott D Solomon, Brian Claggett, Shirley V Wang, Muthiah Vaduganathan
Individualized Treatment Effect Prediction with Machine Learning - Salient Considerations
NEJM evidence
mixed method study developed multiple question types understand measure womens perceived benefit adjuvant endocrine therapy hypothesis patients understand benefit sought develop questions needed test hypothesis obtain initial patient estimates 82022 32023 qualitative interviews focused assessing modifying 9 initial varied question types asking overall survival os benefit adjuvant endocrine therapy subsequent focus groups modified selected optimal questions patients selfassessment os benefit compared individualized predict model results fiftythree patients completed survey 42 hispanic 30 rural 47 income 39999 per year patients reported adequate health care literacy 615 average confidence treatment medication decisions 494 95 ci 244595 original 9 questions 3 modified questions ultimately found capture patients perception os benefit focusing graphical prose styles patients estimated os benefit 42 compared 44 calculated predict model p 0001 group considerable representation ethnic minority rural lowincome patients qualitative data showed one modality question type needed clearly capture patients understanding treatment benefit women breast cancer significantly overestimated 10year os benefit adjuvant endocrine therapy compared predict model