Real-world impact of patient-reported outcome measurement on overall survival, healthcare use and treatment discontinuation in cancer patients
Bibliographic record
Abstract
Aim: The purpose of this retrospective, population-based, observational cohort analysis was to assess whether routine patient-reported outcomes (PRO) monitoring alone has an impact on real-world overall survival (OS) and hospitalizations among individuals diagnosed with lung, breast or colorectal cancer. The importance of follow-up care in post-PRO data collection was also discussed. Patients & methods: Administrative databases covering 17 cancer centers from Alberta, Canada were queried and individuals ≥18 years old and diagnosed with lung, breast or colorectal cancer from 1 January 2016 to 31 December 2019 were included and followed until 31 December 2020. Patients were stratified by whether they received routine PRO monitoring initiated within 120 days of diagnosis and matched 1:1 with use of propensity scores based on baseline characteristics. OS was assessed from the index date to death, and the respective Kaplan–Meier curves were estimated along with hazard ratios from Cox Proportional Hazard Models. Linear and logistic regression models were used to estimate mean differences and odds ratios (OR) respectively for healthcare resource utilization events including cancer physician visits, emergency department visits and outpatient ambulatory care encounters. Results: 4800 patients were included in each matched cohort. There was no statistically significant difference between PRO monitoring and non-monitoring cohorts in OS (HR = 1.01; 95% CI: 0.93–1.09; p = 0.836) and treatment discontinuation (OR = 0.98; 95% CI: 0.85–1.12; p = 0.75). Median OS was 51.5 months for unmonitored cohort (95% CI: 47.5–NA) versus 50.6 months for monitored cohort (95% CI: 47.6–55.7). Compared with PRO-monitored patients, unmonitored patients were associated with lower hospitalization risks (OR = 1.12; 95% CI: 1.03–1.22; p = 0.01). However, PRO-monitored patients experienced significantly fewer physician visits in comparison to unmonitored patients (MD = -1.036; 95% CI: -1.288 to -0.784, p < 0.001). Conclusion: Our results show that capturing patient-reported symptoms alone reduced the number of physician visits but neither reduced hospitalizations nor improved OS in this real-world cancer population. To drive more meaningful clinical impact, PRO monitoring programs must be met with rigorous follow-up response to the identified symptoms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".