The impact of the COVID-19 pandemic on patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) in an Australian outpatient oncology setting.
Bibliographic record
Abstract
195 Background: PROMs and PREMs may be useful tools to reflect the impact of the COVID-19 pandemic on cancer patients’ wellbeing and care. This analysis compares baseline self-reported quality of life (QoL), symptoms and supportive care needs between two independent patient groups based on when and how they attended their oncology appointment: 1) in person, prior to the global declaration of the COVID-19 pandemic and; 2) via telehealth, during the pandemic. Methods: Patients were invited to complete a suite of PROMs and PREMs including the EQ-5D-5L, modified Edmonton Symptom Assessment System-Revised (ESAS-R) and the modified Supportive Care Needs Survey Short-Form (SCNS-SF34) on an iPad in the waiting room before each appointment (pre-COVID-19 pandemic phase, December 2019 to March 2020) or online prior to a telehealth appointment (COVID-19 pandemic phase, October 2020 to April 2021). Descriptive statistics were reported for clinical and demographic factors and the PROMs and PREMs. Baseline scores from pre-COVID-19 and COVID-19 cohorts were compared using t-tests and chi-square tests. Results: In the pre-COVID-19 phase, 100 patients (99 females, 60.7 years old) participated compared with 129 patients (128 females, 59.7 years old) in the COVID-19 phase. Primary cancer diagnoses were breast (pre-COVID-19 68%, COVID-19 71%), gynaecological (pre-COVID-19 31%, COVID-19 37%) and lung (pre-COVID-19 1%) cancers. Mean age, gender, relationship status, language spoken, cancer diagnoses, and staging were similar, all p > 0.05. Median self-rated health (EQ-VAS score) was also similar between the pre-COVID-19 phase (74, IQR 33) and the COVID-19 phase (75, IQR 34), p = 0.51. Median ESAS-R swelling/lymphoedema score was higher for the COVID-19 phase (1, IQR 3) than the pre-COVID-19 phase (0, IQR 3), p = 0.03. Median SCNS standardised psychological domain score was lower for the COVID-19 phase (35, IQR 40) compared with the pre-COVID-19 phase (45, IQR 42), p = 0.03. No other significant differences in symptoms or unmet needs were noted (all p > 0.05). The top three symptoms concerns (ESAS-R score ≥7) were: 1) tiredness (pre-COVID-19 33%, COVID-19 22.7%); 2) sleep problems (pre-COVID-19 24.5%, COVID-19 21.9%); 3) drowsiness (pre-COVID-19 21.2%) and concentration and memory (COVID-19 19.5%). Conclusions: Despite the COVID-19 pandemic, these data reflect the symptoms and concerns impacting on the QoL among Australian oncology patients have remained largely stable. Although Australian COVID-19 case numbers have remained low, PROMs and PREMs are crucial tools for continuing to support oncology patients with QoL and supportive needs in the pandemic era. Clinical trial information: ACTRN12619001470189.
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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".