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Table 7 The aspiration of personalized outcome measurement in rare diseases [90,91,92,93,94,95,96]

From: Measuring what matters to rare disease patients – reflections on the work by the IRDiRC taskforce on patient-centered outcome measures

Moving beyond the standard: Many PCOMs, such as ClinROs or PROs, typically include a standard set of items (or tasks) each rated on a standard set of response options, regardless of the relevance of specific items to each individual patient. When rare disease patients are in very different stages of their disease or when a rare disease is ultra-rare and affects a handful of individuals worldwide, these types of instrument may not have sufficient discriminatory capacity to detect change in clinically meaningful dimensions that are important to patients. In other words, a health outcome or an improvement that is relevant or resonates with one patient, may not with another. Two alternatives currently stand out: Goal Attainment Scaling and Computer Adaptive Testing.

Goal Attainment Scaling (GAS): GAS allows patients and their treating professionals to work together to identify individual treatment goals that have the greatest relevance. A key feature of GAS is the ‘a priori’ establishment of criteria for ‘successful’ outcomes, which are agreed with the patient and family before a health intervention starts so that everyone has a realistic expectation of what is likely to be achieved and agrees that this would be worth striving for. An example of GAS for use in haemophilia (named GOAL-Hem) covers four broad categories: managing haemophilia (e.g. being able to administer factor), haemophilia complications (e.g. bleeds, pain, joint problems), impact on activities, and impact on emotions and relationships. The applicability of each goal area is determined for different age groups (i.e. adults, adolescents, children). For instance, a common goal for paediatric patients (aged <15) is to become competent and responsible for self-infusion of factor concentrate. This goal area can be selected, current baseline ability assessed and quantifiable degrees of improvement described (a priori) to define potential outcomes.

Computer Adaptive Testing (CAT): Whilst CAT has been used most notably in educational testing, the approach has more recently been applied to health outcomes, such as the Patient Reported Outcomes Measurement Information System (PROMIS®) measures and the European Organisation for Research and Treatment of Cancer CAT (EORTC CAT). In CAT, the computer administering the ‘test’ selects questions or ‘items’ from an item bank based on a patient’s response to previously answered questions. Although patients receive different questions based on their individualized responses, scores are standardized and can be compared using a common scale. The goal of CAT is to improve measurement precision for each individual for the specific domain of interest (e.g. physical functioning, depression) being measured using the least number of items.

Prospects: GAS and CAT are promising methodologies. But, nonetheless, in relation to PCOM, these are still in their infancy. Whilst GAS has the potential for greater relevance sensitivity over standard measures, the appropriateness of comparing scores between patients has not been proven yet, and is in fact a real challenge. Alternatively, CAT provides a common frame of reference for direct measurement comparability between patients, but items are selected by the computer algorithms with no recourse to patient preferences. One promising initiative developed for visually impaired patients may provide a bridge between GAS and CAT. As such, the Activity Inventory (AI) is an adaptive visual function CAT that consists of 459 tasks grouped into 50 goals. Visually impaired patients rate the importance of each goal, allowing for a CAT to deliver an individually tailored set of items specific to patients.