The impact of psychosocial intervention on survival in cancer: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: The impact of psychosocial interventions on survival remains controversial in patients with cancer. A meta-analysis of the recent literature was conducted to evaluate the potential survival benefit associated with psychosocial interventions for cancer patients. METHODS: MEDLINE, EMBASE, and Cochrane Central were searched from January 2004 to May 2015 for all randomized controlled trials (RCTs) that compared survival outcomes between cancer patients receiving a psychosocial intervention and those receiving other, or no interventions. Endpoints included one-, two-, and four-year overall survival. Subgroup analyses were performed to compare group-versus individually-delivered interventions, and to assess breast cancer-only trials. RESULTS: Of 5,080 identified articles, thirteen trials were included for analysis. There was a significant survival benefit for the intervention group at one year [risk ratio (RR) =0.82; 95% confidence interval (CI), 0.67-1.00; P=0.04] and two years (RR =0.86; 95% CI, 0.78-0.95; P=0.003). However, no significant difference was detected at four years (RR =0.94; 95% CI, 0.85-1.04; P=0.24). Among patients with breast cancer, there was a significant survival benefit of psychosocial interventions at one year (RR =0.59; 95% CI, 0.42-0.82; P=0.002), but no difference at two years (RR =0.82; 95% CI, 0.67-1.02; P=0.07) or four years (RR =0.95; 95% CI, 0.73-1.23; P=0.68). Group-delivered interventions had a significant survival benefit favouring the intervention group at one year (RR =0.57; 95% CI, 0.41-0.79; P=0.0008), but no difference at two years (RR =0.84; 95% CI, 0.68-1.02; P=0.08) or four years (RR =0.94; 95% CI, 0.75-1.20; P=0.64). Individually-delivered interventions had no significant survival benefit at one year (RR =0.92; 95% CI, 0.79-1.08; P=0.32), two years (RR =0.87; 95% CI, 0.75-1.00; P=0.05), or four years (RR =0.93; 95% CI, 0.84-1.04; P=0.21). CONCLUSIONS: For the main analysis and group-delivered treatments, psychosocial interventions demonstrated only short-term improvements in survival. Individually-delivered interventions failed to show any survival benefit. Future studies with longer follow-up are warranted to investigate long-term survival outcomes.
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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 | 0.020 | 0.040 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.067 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".