Assessing the feasibility of recording smartphone-based patient-reported outcomes in patients with cancer: A pilot study.
Bibliographic record
Abstract
e13528 Background: We conducted this study to evaluate the feasibility of completing patient-reported outcomes (PROs) using a mobile-based secure system at home, as opposed to the traditional method of completing them in crowded outpatient oncology clinics during hospital visits, which may not be ideal in resource-limited settings. Methods: The study included patients aged over 18 years who were newly diagnosed with solid-organ cancer between July 2021 and July 2022 at a tertiary cancer center in India. Patients who were able to use a smartphone were invited to complete a mobile-based Edmonton Symptom Assessment Scale (ESAS) questionnaire, which was accessed via a secure link sent to their phone as a chat. The ESAS questionnaire included physical (six domains: pain, tiredness, drowsiness, shortness of breath, nausea, loss of appetite), psychological (anxiety and depression), and overall well-being (one domain) questions, each rated on a scale of 0-10, with a higher number indicating greater symptom burden. Symptoms were classified as mild (1-3), and moderate to severe (4-10). The primary objective was to determine the completion rate of the questionnaire, while the secondary objectives were to determine the incidence of moderate to severe symptoms, both physical and psychological, at cancer diagnosis. Multivariate logistic regression analysis was used to identify factors associated with moderate to severe symptoms. Results: We reached out to 707 consecutive patients who had recently been diagnosed with solid-organ cancer and used smart phone. The median age of participants was 53 years (with an interquartile range of 43-62 years), and 52.3% were female. Breast cancer (30.6%) was the most common diagnosis, followed by lung cancer (28.8%). Approximately, one-third of all patients had metastatic disease at diagnosis, while others were similarly distributed in stage I-III. Overall, 650 patients (91.9%) patients completed the mobile-based questionnaire; 38.9% of patients had moderate to severe physical symptoms and 30.9% had moderate to severe psychological symptoms. Pain (57.7%) and tiredness (58.7%) were the most commonly reported physical symptoms in moderate to severe category, while nausea (18.1%) and drowsiness (20.3%) were reported least frequently as moderate to severe. Anxiety (35.1%) was more prevalent than depression (26.1%). The total symptom score was mild in 76.5% of patients and moderate to severe in 18.8%. On multivariate logistic regression, patients with advancing age, female sex, and metastatic disease at diagnosis were more likely to report moderate to severe symptoms. Conclusions: Using smartphone-based PROs can be an efficient way to record symptoms in cancer patients, and their high completion rates make them suitable for routine use in oncology clinics, especially considering the increasing number of smartphone subscribers globally.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".