Patient-reported outcomes to assess symptoms in patients with metastatic breast cancer: Pilot implementation project.
Bibliographic record
Abstract
177 Background: Use of patient-reported outcomes (PRO) to evaluate symptoms improves clinical outcomes. Best practices for implementing PROs into routine care may vary according to clinical scenario, site-specific resources and programmatic goals. Patients with metastatic breast cancer (MBC) often experience a variety of symptoms. Methods: As a quality improvement project, we are pilot testing incorporation of a battery of PRO measures into routine care for patients with MBC at Johns Hopkins in order to gain experience that will guide future broader implementation of PROs across our program. Participants complete the PROs on paper at baseline (BL), 3, and 6 months (mo). Measures include NCCN Distress Thermometer (BL only), Patient Health Questionnaire-8 (PHQ-8), Generalized Anxiety Disorder-7 (GAD-7), PRO-CTCAE Insomnia questions and a modified version of the revised Edmonton Symptom Assessment System (r-ESAS) questionnaire with 3 extra symptom domains. Project team members alert clinicians by email of scores that exceed severity thresholds as follows – Distress: ≥4, PHQ-8: ≥8, GAD-7: ≥10, any item on r-ESAS: ≥4 and PRO-CTCAE Insomnia: severe/very severe or quite a bit/very much. Results: From May 29, 2020 and April 5, 2021, 67 patients were approached for participation, and 40 (59.7%) completed the BL PROs. Median age was 64 (range 36-85). Most participants were White (70%), non-Hispanic (90%) and had hormone receptor-positive (93%) MBC. At BL, 22 (55%) had visceral disease and most were receiving endocrine-based regimens [21 (53%)] or chemotherapy [16 (40%)]. 27 (68%) participants had ≥1 BL alert. The most common BL alerts were for symptoms on the r-ESAS [23 participants (58%)]. The most frequent items on the r-ESAS for which participants had BL alerts were pain, tiredness, well-being, tingling/numbness and rash. Other BL alerts were: Distress [9 participants (23%)], PRO-CTCAE Insomnia [5 participants (13%)], PHQ-8 [4 participants (10%)] and GAD-7 [2 participants (5%)]. To date, 24 of 35 (69%) and 15 of 28 (54%) participants who have reached the 3 and 6 mo time points have completed the respective follow-up (FU) PROs. Most common FU alerts to date are on the r-ESAS [3 mo: 14 participants (58%), 6 mo: 9 participants (60%)]. The project team has successfully notified providers of all alerts to date. Clinical actions (phone calls, provider visits and/or referrals) have been taken within 30 days of notification for > 75% of alerts. Conclusions: Implementation of a PRO battery for patients receiving routine care for MBC led to detection of a range of symptoms, the majority of which were clinically actionable. Restrictions on in-person interactions during the COVID-19 pandemic may have contributed to low rates of PRO completion in this pilot project. Prior to broader implementation, we will consider strategies such as an electronic platform and a shorter battery to enhance patient engagement.
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 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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".