Psycho-oncology/Supportive Care in Head–Neck Cancers Patients Undergoing Radiation Therapy: A Randomized Controlled Trial
Bibliographic record
Abstract
Abstract An elevated level of distress is associated with poor health-related quality of life (QoL), decreased patient satisfaction, poor treatment compliance, and possible reduced survival. This randomized trial, conducted at a single center in India, enrolled head–neck cancer patients aged > 18 years who were undergoing curative intent radiation therapy, and had significant baseline distress as per the National Comprehensive Cancer Network distress thermometer (distress score ≥ 4). The patients were randomized into the Standard arm (STD), which involved routine assessment by the oncologist, or the Interventional arm (INV), where psycho-oncology/palliative/supportive care referral was done at baseline and every week during treatment. The study's primary endpoint was the proportion of patients having significant distress 6 months' posttreatment. A total of 212 patients were randomized (n = 108 STD, n = 104 INV). At 6 months' post-treatment completion, 90 and 89 were evaluable in the STD and INV, respectively. The median distress score was 2 in both arms at this time point. There was no significant difference in the proportion of patients having significant distress in STD versus INV (9 vs. 15.6%, p = 0.20). There was an improvement in any symptom measured by the Edmonton Symptom Assessment Score (pain, tiredness, drowsiness, nausea, lack of appetite) and the QoL for the entire cohort with no statistically significant difference between arms for symptoms, QoL, or survival endpoints. Psycho-oncology and palliative/supportive care referral did not impact distress, symptom burden, QoL, or survival at 6 months' posttreatment completion significantly in this randomized trial. Clinical Trial Registry of India Registration number: CTRI/2016/01/006549.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".