The impact of symptom screening on survival among patients with cancer across varying levels of pre‐diagnosis psychiatric care
Bibliographic record
Abstract
BACKGROUND: Patients diagnosed with cancer often experience considerable challenges with mental health, and those who had more intense psychiatric care prior to their cancer diagnosis have a higher risk of mortality. As prior research demonstrated a survival benefit among patients screened for symptoms using the Edmonton symptom assessment system (ESAS), this study aims to examine the association between being ESAS-screened and the risk of mortality across varying intensity levels of pre-diagnosis psychiatric care utilization. METHODS: We conducted a retrospective matched cohort study using population-wide administrative databases. All patients diagnosed with cancer in Ontario, Canada, from January 2007 to December 2015 were identified. Propensity score matching was used to pair ESAS-screened individuals to those not screened. Pairs were also hard matched on a pre-diagnosis psychiatric care utilization gradient. A multivariable Cox proportional hazards regression model was implemented to estimate the association between ESAS and mortality, for each intensity level of pre-diagnosis psychiatric care. RESULTS: The matched cohort consisted of 119,806 patient pairs (ESAS-screened and not screened), of whom 54,468 (45.5%) pairs had prior outpatient psychiatric care and 2249 (1.8%) pairs had experienced emergency department visits or had been hospitalized for psychiatric care. Overall being exposed to ESAS was significantly associated with a 51% decrease in the hazard of mortality (HR 0.49, 95%CI 0.48-0.50, p-value <0.0001). This association was similar across all levels of prior psychiatric use, however, there was no evidence of a differential impact. CONCLUSION: In addition to routinely monitoring symptom severity, including depression, among patients with cancer, it is also important to identify those with preexisting psychiatric comorbidities at the time of diagnosis. This information can be used to ensure that timely and appropriate psycho-oncology services and psycho-social supports are offered to help the patient and their family cope during the cancer disease trajectory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".