Improving Quality of Life Based on Electronic Patient Reported Outcomes in Patients with CLL and MDS: The Mypal Study
Bibliographic record
Abstract
Introduction: Palliative care is a critical component of care for patients with chronic hematological malignancies. Leveraging eHealth approaches can potentially facilitate the delivery of palliative care, leading to improved quality of life (QoL). Methods: The MyPal study (NCT04370457) is a randomized controlled clinical trial assessing an eHealth intervention on QoL of patients. The study was conducted according to the Declaration of Helsinki. The ethical aspects of the study, given the vulnerability of the patients, were addressed with diligence and approvals were obtained from the appropriate Research Ethics Committees. Patients who were receiving or had previously received treatment for CLL or MDS were randomly assigned (1:1) to access the MyPal platform versus standard of care. The MyPal platform included a smartphone application used to report QoL status (ePRO questionnaires) and symptoms. The primary endpoint was QoL at 12 months, assessed by the European Organization for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 General Questionnaire and the Euroqol 5-dimension (Euroqol EQ-5D-3L). Secondary endpoints included physical and emotional functioning, measured by the Integrated Palliative Care Outcome Scale (IPOS), satisfaction with care, measured by the EORTC Patient Satisfaction with Cancer Care questionnaire PATSAT-C33 (PATSAT-C33), and overall survival (OS). Additionally, the Edmonton Symptom Assessment System (ESAS), the Brief Pain Inventory (BPI), and the Emotion Thermometers (ET) QoL questionnaires were assessed only in the intervention group. Results: A total of 171 patients (97 and 74 in the control and intervention arms, respectively) who answered multiple questionnaires were included in the analysis. The intervention group reported a significant decrease in pain (β2=-0.48 (-0.77, -0.19), p<0.001) compared to the control group (β1=0.3 (0.09, 0.5), p=0.01) as measured by the EORTC QLQ-C30. Communication and pain as measured by IPOS reduced equally in both groups [β2=0 (-0.03, 0.02), p=0.82; β2=-0.01 (-0.02, 0), p=0.1, respectively]. Family involvement significantly increased over time only for the intervention group [β2=0.32 (0.01, 0.64), p=0.042]. The other items of EORTC QLQ-C30, Euroqol EQ-5D-3L, IPOS, and PATSAT-C33 remained unchanged in both groups. The intervention group displayed a statistically significant improvement in all ESAS, BPI, and ET scales. The estimated absolute improvement between the first and last assessment was 1.68, 2.16, 0.96, 1.44, 1.68, and 0.96 points for pain, tiredness, nausea, drowsiness, appetite loss, and shortness of breath, respectively, and 0.96, 1.2 and 1.2 for depression, anxiety, and well-being, respectively. The estimated absolute improvement between the first and last assessment for both pain severity and the interference items of the BPI was 1.2 points. Finally, distress, anxiety, depression, anger, and need for help showed a statistically significant reduction over time and an absolute improvement between the first and last assessment of 1.68, 1.92, 1.2, 1.2, and 0.72 points, respectively. After 12 months, in the ITT, 6 (6.2%) patients died in the control arm and 5 (6.3%) in the intervention arm. Conclusion: The MyPal tools improved several aspects of QoL for patients with CLL and MDS while also promoting family involvement in palliative care.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".