PMON258 Patient-Reported Outcomes for men with Hypogonadism and the Impact of Low Testosterone Levels: a review of measures
Bibliographic record
Abstract
Abstract Background To better understand the impact of low testosterone treatments on men with hypogonadism, data on treatment efficacy and safety must be combined with patient-reported outcomes measurements (PROMs). Whether these objective tools conceptualise and measure the impacts of hypogonadism in the same way, is not known. Aim To appraise the evidence on the item content of validated patient-reported outcome measures for hypogonadism evaluations and identify core domains of potential importance in this context. Methods We systematically reviewed tools (e.g., questionnaires, surveys, scales) in published quantitative or qualitative data of men with low testosterone and/or those using (or who had considered treatment). PROMs data extraction forms and data tables were generated for each stage of the extraction process to standardise the information recorded and aid analysis. Data was synthesised by classifying the items identified into domains determined by the nomenclature reported in included studies and the International Classification of Functioning, Disability and Health (WHO-ICF). Finally, a narrative synthesis of the instruments and their inter-related domains and subdomains was conducted to identify areas of both convergence and divergence. Results A total of nine tools measuring PROMs of men with low testosterone were included in this review. The included studies were set within the US (n=5), Canada (n=1), UK (n=1), Germany (n=1), Italy (n=1). The tools identified were: Androgen Deficiency in Aging Males (ADAM) Questionnaire, The Aging Males’ Symptoms (AMS) scale, ANDROTEST ©, The Age-Related Hormone Deficiency Dependent Quality of Life Questionnaire (A-RHDQoL)©, Hypogonadism Energy Diary (HED), Hypogonadism Impact of Symptoms Questionnaire (HIS-Q), HIS-Q-Short Form (HIS-Q-SF), Massachusetts Male Ageing Study (MMAS) questionnaire, Sexual Arousal, Interest, and Drive Scale (SAID). Only HED, SAID, and HIS-Q reported including patients while developing the tool. The number of items varied across instruments and ranged from 3 to 53 items (median=7) with a cumulative total of 98 individual items. The ten domains identified were: Cognition, Energy, General well-being, Mood, Pain, Physical-General, Role, Sexual, Sleep, Social. Across tools, the most frequently identified domain was the sexual domain. However, two of the PROMs, HED and MMAS, did not include any items that covered the sexual domain. Six of the nine tools were considered multi-dimensional, and three were considered unidimensional (i.e. only capturing one domain). The A-RHDQoL tool showed to be the most comprehensive tool across the PROMs included since this was the only one to include items that could be coded to all ten domains. Conclusions This study has demonstrated the considerable item concept variability across disease-specific PROMs for men with low testosterone regarding development and domain coverage. The dominant focus of these PROMs to date has centred around sexual function, but possibly to the detriment of other aspects that also matter to patients. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".