Towards global consensus on core outcomes for hidradenitis suppurativa research: an update from the HISTORIC consensus meetings I and II

Background A core outcomes set (COS) is an agreed minimum set of outcomes that should be measured and reported in all clinical trials for a specific condition. Hidradenitis suppurativa (HS) has no agreed‐upon COS. A central aspect in the COS development process is to identify a set of candidate outcome domains from a long list of items. Our long list had been developed from patient interviews, a systematic review of the literature and a healthcare professional survey, and initial votes had been cast in two e‐Delphi surveys. In this manuscript, we describe two in‐person consensus meetings of Delphi participants designed to ensure an inclusive approach to generation of domains from related items. Objectives To consider which items from a long list of candidate items to exclude and which to cluster into outcome domains. Methods The study used an international and multistakeholder approach, involving patients, dermatologists, surgeons, the pharmaceutical industry and medical regulators. The study format was a combination of formal presentations, small group work based on nominal group theory and a subsequent online confirmation survey. Results Forty‐one individuals from 13 countries and four continents participated. Nine items were excluded and there was consensus to propose seven domains: disease course, physical signs, HS‐specific quality of life, satisfaction, symptoms, pain and global assessments. Conclusions The HISTORIC consensus meetings I and II will be followed by further e‐Delphi rounds to finalize the core domain set, building on the work of the in‐person consensus meetings

Mixture dynamics: Combination therapy in oncology

In recent years combination therapies have become increasingly popular in most therapeutic areas. We present a qualitative and quantitative approach and elucidate some of the challenges and solutions to a more optimal ther- apy. For tumor growth this involves the study of semi-mechanistic cell-growth/kill models with multiple sites of action. We introduce such models and analyze their dynamic properties using simulations and mathematical analysis. This is done for two specific case studies, one involving a single compound and one a combination of two compounds. We generalize the notion of Tumor Static Concentration to cases when two compounds are in- volved and develop a graphical method for determining the optimal combination of the two compounds, using ideas akin to those used in studies employing isobolograms. In studying the dynamics of the second case study we focus, not only on the different concentrations, but also on the different dosing regimens and pharmacokinet- ics of the two compounds. Analysis and Stochastic