Integrating PROs with prognostic value into oncologic care: High ESAS global distress score associated with lower overall survival in advanced cancer patients.
Bibliographic record
Abstract
12021 Background: Despite compelling data supporting their use, patient reported outcomes (PROs) are not widely integrated into routine cancer care. In our Palliative Care (PC) practice, all patients complete the Edmonton Symptom Assessment Scale (ESAS), a simple, validated 10-item PRO tool which uses a 0 to 10 rating of 10 common symptoms (pain, fatigue, nausea, drowsiness, appetite, sleep, dyspnea, well-being, anxiety & depression). Our team has previously validated the Global Distress Score (GDS), a sum of 9 physical + psychosocial ESAS items. Here, we studied the implementation of the GDS as a streamlined way to capture the overall symptom burden while providing prognostic value. Methods: We queried a PC database for patients w metastatic cancer at time of 1st PC visit. GDS was calculated & grouped into 3 cohorts based on previous work & clinical experience: high (GDS of 35+), Moderate (16-34) or Low (0-15). Overall Survival was defined as time from 1st PC visit date to death. Regression analysis, ANOVA and t-tests were conducted. Results: 333 patients met the inclusion criteria: median age 62.4y (range 20.5-88.4y), 25 AYA (15-39y), 169 mid age (35-64y), 140 seniors (65y+); 190 female 143 male; median prior therapies 2 (range 0-11), 227 patients were in 2nd line + above therapy. Median ECOG PS 2; 124 patients w ECOG PS 3 & 33 w ECOG PS 4. 262 patients had died at time of analysis. Lower OS was associated w higher GDS (r 0.21, P < 0.001). OS in Low, Mod, High GDS cohorts was 13.1m, 7.9m, & 3.7m, respectively (p < 0.001). There were no sig OS difference between 3 age cohorts (AYA 5.2m, mid age 6m, seniors 5.4m, p0.56). Conclusions: Higher GDS score was associated with a clinically significant decrease in overall survival highlighting the potential of the ESAS as a PRO tool in prognostication and clinical decision making for patients with advanced cancers with a high symptom burden. In the realm of increasingly complex PRO instruments, the ESAS represents a simple, well-validated tool which, in our studies and 25 years of clinical experience, takes the patient less than a minute to complete, with subscores such as the GDS which carry a highly prognostic utility for patients with advanced cancers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".