Pattern of analgesic prescriptions and pain-related outcomes in older patients with cancer: A retrospective observational study
Bibliographic record
Abstract
Background: Adequate pain management in patients with cancer is crucial, as uncontrolled pain affects their physical and psychological well-being, and impacts sleep, activities of daily living (ADL), and quality of life. Objectives: This study aimed to evaluate the prevalence of untreated pain, pattern of analgesic use, and physical and psychological deficits related to pain in older patients with cancer who had moderate or severe pain. Materials and Methods: This was a retrospective observational study conducted between February 2022 and April 2023 in the geriatric oncology clinic of the Department of Medical Oncology at the Tata Memorial Hospital in Mumbai, India. Pain intensity, type of analgesics consumed, anxiety (measured by the Generalized Anxiety Disorder Questionnaire-7), depression (measured by the Geriatric Depression Scale: Short Form), sleep disturbance (Yes/No question), and functional deficits (measured by the Katz Index of Independence in Activities of Daily Living, Lawton Instrumental activities of Daily Living Scale, and Timed Up and Go Test) were captured from the dataset. Pain intensity was assessed using the Edmonton Symptom Assessment System (ESAS), in which “0” indicated “no pain” and “10” indicated the “worst possible pain.” A pain intensity score of 4 or more was considered significant; scores from 4-7 were categorized as moderate pain, and 8-10 as severe pain. Results: We evaluated 1203 patients in the geriatric oncology clinic and enrolled 321 (26.7%) who had reported pain intensity of 4 or higher 260 (21.6%) had moderate pain, and 61 (5.1%) had severe pain. The mean pain score was 5.8 (standard deviation, 1.6). Higher pain scores were associated with higher prevalence of anxiety, depression, sleep disturbance, and functional deficits. There were 158 (49.2%) patients who had not been prescribed any pain medication. Analgesics prescribed for the 260 patients with moderate pain included opioids ( n =14; 5.4%), non-opioids ( n =35; 13.5%), combined opioids and non-opioids ( n =71; 27.3%), and no treatment ( n =140; 53.8%). Analgesics prescribed for the 61 patients with severe pain included opioids ( n =4; 6.6%), non-opioids ( n =16; 26.2%), combined opioids and non-opioids ( n =23; 37.7%), and no treatment ( n =18; 29.5%). Overall, tramadol ( n =76; 67.9%) and non-steroidal anti-inflammatory drugs ( n =93; 64.1%) were the most frequently used analgesics. Conclusion: Pain affects the mental and physical wellbeing of older patients with cancer. Over half of the older Indian patients with cancer who have moderate pain and about a third with severe pain are not on any analgesics. This is an urgent unmet need, and assessment of pain must become part of the routine evaluation of all patients. (Clinical Trials Registry-India: CTRI/2020/04/024675).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".