The PROMIS of QALYs

Hanmer, Janel; Feeny, David; Fischhoff, Baruch; Hays, Ron D.; Hess, Rachel; Pilkonis, Paul A.; Revicki, Dennis A.; Roberts, Mark S.; Tsevat, Joel; Yu, Lan

doi:10.1186/s12955-015-0321-6

Cited by 51 publications

(44 citation statements)

References 11 publications

(9 reference statements)

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“…In addition to future validation work that is needed to assess their scoring system in different samples, algorithms have been developed in the PROMIS project to estimate the EO-5D-3L [25] and the HUI-3 [26] from the PROMIS-29 scales. Preference-based scoring functions can also be estimated directly from the PROMIS-29 [27-29]. …”

Section: Discussionmentioning

confidence: 99%

Adapting summary scores for the PROMIS-29 v2.0 for use among older adults with multiple chronic conditions

et al. 2018

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Section: Discussionmentioning

confidence: 99%

Adapting summary scores for the PROMIS-29 v2.0 for use among older adults with multiple chronic conditions

et al. 2018

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“…A potential barrier to achieving this goal is that programs may be required to pay licensing fees to use some of the current standard measures, although fees may be discounted for non-commercial users. Alternative HRQoL measures are available without cost from the World Health Organization and the National Institutes of Health PROMIS initiative (Hays, Bjorner, Revicki, Spritzer, & Cella, 2009), but there is not yet an accepted approach to using these measures to calculate QALYs (Hanmer et al, 2015). The lack of HRQoL evidence prevents opioid treatment programs from assessing the full impact of treatment on patients’ lives and limits their ability to fully capture the value of investments in opioid use disorder treatments.…”

Section: Discussionmentioning

confidence: 99%

Quality of life as an outcome of opioid use disorder treatment: A systematic review

Bray

Aden

Eggman

et al. 2017

Journal of Substance Abuse Treatment

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Background and aims The recent opioid epidemic has prompted renewed interest in opioid use disorder treatment, but there is little evidence regarding health-related quality-of-life (HRQoL) outcomes in treatment programs. Measuring HRQoL represents an opportunity to consider outcomes of opioid use disorder treatment that are more patient-centered and more relevant to overall health than abstinence alone. We conducted a systematic literature review to explore the extent to which the collection of HRQoL by opioid treatment programs is documented in the treatment program literature. Materials and methods We searched PubMed, Embase PsycINFO and Web of Science for papers published between 1965 and 2015 that reported HRQoL outcome measures from substance abuse treatment programs. Results Of the 3014 unduplicated articles initially identified for screening, 99 articles met criteria for further review. Of those articles, 7 were unavailable in English; therefore 92 articles were reviewed. Of these articles, 44 included any quality-of-life measure, 17 of which included validated HRQoL measures, and 10 supported derivation of quality-adjusted life year utility weights. The most frequently used validated measure was the Addiction Severity Index (ASI). Non-U.S. and more recent studies were more likely to include a measure of HRQoL. Conclusions HRQoL measures are rarely used as outcomes in opioid treatment programs. The field should incorporate HRQoL measures as standard practice, especially measures that can be used to derive utility weights, such as the SF-12 or EQ-5D. These instruments provide policy makers with evidence on the impact of programs on patients’ lives and with data to quantify the value of investing in opioid use disorder treatments.

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“…A previous study used discrete choice experiments to derive preferences for health states derived from the PROMIS-29 V.1, but the estimates produced were implausible—the mean was 0.16 in a sample drawn from the U.S. general population [32]. Potentially better alternative methods for directing eliciting preferences in PROMIS have been proposed [33]. …”

Section: Discussionmentioning

confidence: 99%

Using Linear Equating to Map PROMIS® Global Health Items and the PROMIS-29 V2.0 Profile Measure to the Health Utilities Index Mark 3

Hays

Revicki²,

Feeny

et al. 2016

PharmacoEconomics

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Background Preference-based health-related quality of life scores are useful as outcome measures in clinical studies, for monitoring health of populations, and for estimating quality-adjusted life years. Methods This was a secondary analysis of data collected in an internet survey as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®) project. We used the 10 PROMIS global health items, the PROMIS-29 V. 2 single pain intensity item and 7 multi-item scales (physical functioning, fatigue, pain interference, depressive symptoms, anxiety, ability to participate in social roles and activities, sleep disturbance), and the PROMIS-29 V. 2 items to estimate HUI-3 preference scores. Linear regression analyses were used to identify significant predictors, followed by simple linear equating to avoid regression to the mean. Results The regression models explained 48% (global health items), 61% (PROMIS-29 V. 2 scales) and 64% (PROMIS-29 V. 2 items) of the variance in the HUI-3 preference score. Linear equated scores were similar to observed scores, although differences tended to be larger for older study participants. Conclusions HUI-3 preference scores can be estimated from the PROMIS global health items or the PROMIS-29 V. 2. The estimated HUI-3 scores from the PROMIS health measures can be used for economic applications and as a measure of overall health-related quality of life in research.

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The PROMIS of QALYs

Cited by 51 publications

References 11 publications

Adapting summary scores for the PROMIS-29 v2.0 for use among older adults with multiple chronic conditions

Adapting summary scores for the PROMIS-29 v2.0 for use among older adults with multiple chronic conditions

Quality of life as an outcome of opioid use disorder treatment: A systematic review

Using Linear Equating to Map PROMIS® Global Health Items and the PROMIS-29 V2.0 Profile Measure to the Health Utilities Index Mark 3

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