The psychological impact of the COVID-19 pandemic on multiple myeloma patients
Bibliographic record
Abstract
Content: As multiple myeloma (MM) therapies advance, understanding patients', caregivers' and physicians' perspectives on, and satisfaction with, available treatment options, and the impact of these options on quality of life (QoL), is important. EASEMENT is a real-world, observational, cross-sectional study conducted in the UK, Canada and Italy using retrospective chart reviews and surveys. The primary objectives were to describe patient and caregiver QoL (EuroQol 5-dimension 5-level questionnaire [EQ-5D-5L]), patient preference for oral or injectable therapies (single discrete-choice question) and patient satisfaction (Treatment Satisfaction Questionnaire for Medication-9 items [TSQM-9];convenience, effectiveness and global satisfaction subscales;score range 0 100, indicating lower-to-higher satisfaction) by newly diagnosed MM (NDMM) or relapsed/refractory MM (RRMM) status and by investigator-classified treatment injectable-containing ( injectables') versus fully oral ( orals'). A secondary objective was to compare direct healthcare resource utilisation (HRU) between injectable and oral treatments. Descriptive/unadjusted data are presented. 399 patients were enrolled, including 192 NDMM and 206 RRMM patients (status missing for 1 patient). Median age was 71 years (interquartile range 64 76), 61% were male, 74% were retired, 24% had an Eastern Cooperative Oncology group performance status ?2 and 51%/41% were/were not living with their caregiver (8% missing). At the time of study visit, among NDMM patients, 77% were receiving injectables and 23% orals (treatment regimens are summarised in the Table). 9% of NDMM patients preferred injectables and 34% orals (52% no preference, 5% missing). Among RRMM patients, 42% were receiving injectables and 58% orals (treatment regimens are summarised in the Table). 3% of RRMM patients preferred injectables and 55% orals (34% no preference, 7% missing). There were no differences in treatment satisfaction between NDMM and RRMM patients. Results from the TSQM domains are reported for injectables versus orals, respectively;mean convenience score was significantly lower (74.7 vs 78.3;P = 0.0414);mean TSQM perception of effectiveness (72.4 vs 74.7;P = 0.3857) and global satisfaction (72.1 vs 74.2;P = 0.1948) scores did not differ. QoL dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) were not significantly different between NDMM and RRMM patients or between patients receiving injectables or orals. When patients were asked to rate their health on a visual analogue scale (range 0, worst imaginable health, to 100, best imaginable health, as perceived by patients), mean score was significantly higher in NDMM versus RRMM patients (68.0 vs 63.1, P = 0.0313), but similar between patients receiving injectables versus orals (65.0 vs 66.2, P = 0.9069). Preliminary HRU data suggest that the rate of outpatient visits related to MM and its complications was numerically higher among patients receiving injectables versus orals (2.6 vs 2.3 outpatient visits per patient during the last 6 months or since RR disease). EASEMENT data indicate patients' perceived greater convenience with orals versus injectables and that more patients prefer orals versus injectables. Patients receiving orals versus injectables required a numerically lower rate of outpatient visits. Orals are useful options for patients who cannot, or prefer not to, travel to clinics, especially in the context of the COVID-19 pandemic.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".