Finding what is not there
Bibliographic record
Abstract
In a recently published randomized trial, Andersen et al. claimed to observe a reduced risk of recurrence and improved survival among women with early stage breast cancer who were assigned to a psychological intervention versus an assessment-only group. Anderson et al. concluded that "psychological intervention, as delivered and studied here, can improve survival." The current commentary challenges that conclusion on methodological and statistical grounds, noting that the study by Andersen et al. was not designed to assess survival and used methods that capitalized on chance, making it highly unlikely that their claims could be replicated. No other study designed to assess whether psychosocial intervention provides a survival benefit for cancer patients has ever demonstrated such an effect; and, currently, there is no support for the hypothesis that survival benefits can be attributed to psychosocial intervention. The authors of this commentary argue that much needs to be learned at the more basic biobehavioral level about the impact of stress or psychological factors on tumor biology before even considering whether large clinical trials are warranted. In addition, making the claim that psychological interventions improve survival is not evidence-based, is potentially harmful, and detracts from the potential significant benefits of psychological interventions related to quality of life.
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 | 0.040 | 0.218 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.036 | 0.030 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".