The FACT-8D, a new cancer-specific utility algorithm based on the Functional Assessment of Cancer Therapies-General (FACT-G): a Canadian valuation study

United States Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument

OBJECTIVES

To develop a value set reflecting the United States (US) general population's preferences for health states described by the Functional Assessment of Cancer Therapy (FACT) eight-dimensions preference-based multi-attribute utility instrument (FACT-8D), derived from the FACT-General cancer-specific health-related quality-of-life (HRQL) questionnaire.

METHODS

A US online panel was quota-sampled to achieve a general population sample representative by sex, age (≥ 18 years), race and ethnicity. A discrete choice experiment (DCE) was used to value health states. The valuation task involved choosing between pairs of health states (choice-sets) described by varying levels of the FACT-8D HRQL dimensions and survival (life-years). The DCE included 100 choice-sets; each respondent was randomly allocated 16 choice-sets. Data were analysed using conditional logit regression parameterized to fit the quality-adjusted life-year framework, weighted for sociodemographic variables that were non-representative of the US general population. Preference weights were calculated as the ratio of HRQL-level coefficients to the survival coefficient.

RESULTS

2562 panel members opted in, 2462 (96%) completed at least one choice-set and 2357 (92%) completed 16 choice-sets. Pain and nausea were associated with the largest utility weights, work and sleep had more moderate utility weights, and sadness, worry and support had the smallest utility weights. Within dimensions, more severe HRQL levels were generally associated with larger weights. A preference-weighting algorithm to estimate US utilities from responses to the FACT-General questionnaire was generated. The worst health state's value was -0.33.

CONCLUSIONS

This value set provides US population utilities for health states defined by the FACT-8D for use in evaluating oncology treatments.

Psychometric validation of the French Multidimensional Chronic Asthenia Scale (MCAS) in a sample of 621 patients with chronic fatigue

BACKGROUND

Psychometric validation of the Multidimensional Chronic Asthenia Scale (MCAS) was conducted in order to provide an effective tool for assessing the health-related quality of life of French-speaking patients with chronic asthenia (CA).

METHODS

Items resulting from the initial formulation of the self-reported MCAS (along with other materials) were completed by French-speaking volunteers with inactive or active inflammatory bowel disease (IBD-I vs. IBD-A) or chronic fatigue syndrome (CFS). Responses from 621 participants (180 patients with IBD-A, 172 with IBD-I, 269 with CFS) collected in a single online survey were divided into three subsamples to test the construct validity of the MCAS (Step 1, N = 240), to confirm its factorial structure (Step 2, N = 204) and to explore its convergent-discriminant validity with the Fatigue Symptoms Inventory (FSI) and revised Piper Fatigue Scale (r-PFS, Step 3, N = 177).

RESULTS

Steps 1 and 2 showed that, as expected, MCAS has four dimensions: feeling of constraint (FoC), physical (PC), life (LC) and interpersonal consequences (IC), which are also related to the duration of CA (i.e., the longer it lasts, the more the dimensions are impacted). The results further showed that the MCAS is sensitive enough to capture between-group differences, with the CFS group being the most impaired, followed by IBD-A and IBD-I. While convergent-discriminant validity between the 4 factors of MCAS and FSI and r-PFS, respectively, was satisfactory overall, Step 3 also pointed to some limitations that call for future research (e.g., shared variances between the PC and IC dimensions of MCAS and behavioral dimension of r-PFS).

CONCLUSION

Despite these limitations, the MCAS clearly constitutes a promising tool for measuring quantitative differences (i.e., severity/intensity) in CA associated with various diseases, but also, and importantly, the clinically important differences in domains of its expression (i.e., qualitative differences).