Randomized trial of a symptom monitoring intervention for hospitalized patients with advanced cancer (NCT03396510).
Bibliographic record
Abstract
12014 Background: Hospitalized patients with advanced cancer experience a high symptom burden, which is associated with poor clinical outcomes and increased health care use. Symptom monitoring interventions are increasingly becoming standard of care in oncology, but studies of these interventions in the hospital setting are lacking. We evaluated the impact of a symptom monitoring intervention in hospitalized patients with advanced cancer. Methods: We randomly assigned hospitalized patients with advanced cancer who were admitted to the oncology service to a symptom monitoring intervention or usual care. Patients in both arms reported their symptoms (Edmonton Symptom Assessment System [ESAS] and Patient Health Questionnaire 4 [PHQ4], higher scores on both indicate greater symptom severity) daily via tablet computers. Patients assigned to the intervention had their symptom reports presented graphically with alerts for moderate/severe symptoms during daily oncology rounds. The primary endpoint was the proportion of days with improved symptoms for those who completed two or more days of symptoms. Secondary endpoints included hospital length of stay (LOS) and readmission rates. Results: From 2/2018-10/2019, we randomized 390 patients (76.2% enrollment rate); 320 completed two or more days of symptoms (median age=65.6 [range 18.8-93.2]; 43.8% female). The most common cancers were gastrointestinal (36.9%), lung (18.8%), and genitourinary (12.2%). Nearly half of patients (48.5%) had one or more comorbid conditions in addition to cancer. We found no significant differences between intervention and usual care regarding the proportion of days with improved ESAS total (B=-0.05, P=.17), ESAS physical (B=-0.02, P=.52), PHQ4 anxiety (B=-0.03, P=.33), and PHQ4 depression (B=-0.02, P=.44) symptoms. Intervention patients also did not differ from usual care with respect to secondary endpoints of hospital LOS (7.50 v 7.59 days, P=.88) and readmission rates within 30 days of discharge (32.5% v 25.6%, P=.18). Conclusions: For hospitalized patients with advanced cancer, this symptom monitoring intervention did not have a significant impact on their symptom burden and health care use. These findings do not support the routine integration of this type of symptom monitoring intervention for hospitalized patients with advanced cancer. The positive outcomes seen in previous studies of symptom monitoring interventions may not be reproduced in other patient populations and care settings. Support: UG1CA189823; Clinical trial information: NCT03396510 .
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.003 |
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".