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Record W2033765825 · doi:10.1136/ebn.5.3.82

Supportive expressive group therapy did not prolong survival in metastatic breast cancer

2002· letter· en· W2033765825 on OpenAlexaffabout
Bernice King, Becky Fairfield

Bibliographic record

VenueEvidence-Based Nursing · 2002
Typeletter
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsHamilton Regional Laboratory Medicine ProgramHamilton Health Sciences
Fundersnot available
KeywordsMedicineBreast cancerPsychosocialAxillaGynecologyInternal medicineMoodCancerPsychiatry

Abstract

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Goodwin PJ, Leszcz M, Ennis M, et al. The effect of group psychosocial support on survival in metastatic breast cancer. N Engl J Med2001 Dec 13; 345 : 1719 –26 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: In women with metastatic breast cancer, does supportive expressive group therapy (SEGT) prolong survival, improve mood, and reduce pain? Randomised {allocation concealed}*, blinded (assessors of psychosocial outcomes), controlled trial with 12 months of follow up. 7 cancer centres in Canada. 235 women (mean age 50 y) who had histological confirmation of breast cancer and had metastases outside of the breast and ipsilateral axilla. Exclusion criteria were central nervous system metastases; active psychosis, untreated major depression, or severe character disorder; planned participation in a therapist led support group for metastatic breast cancer outside of the study centre; residence >1 hour travel from the study centre; life expectancy <3 months; or inability to speak and read English. Follow up was complete for survival; follow up for psychosocial outcomes was 65% to 71%. Women were … [1]: {openurl}?query=rft.jtitle%253DNew%2BEngland%2BJournal%2Bof%2BMedicine%26rft.stitle%253DNEJM%26rft.aulast%253DGoodwin%26rft.auinit1%253DP.%2BJ.%26rft.volume%253D345%26rft.issue%253D24%26rft.spage%253D1719%26rft.epage%253D1726%26rft.atitle%253DThe%2BEffect%2Bof%2BGroup%2BPsychosocial%2BSupport%2Bon%2BSurvival%2Bin%2BMetastatic%2BBreast%2BCancer%26rft_id%253Dinfo%253Adoi%252F10.1056%252FNEJMoa011871%26rft_id%253Dinfo%253Apmid%252F11742045%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1056/NEJMoa011871&link_type=DOI [3]: /lookup/external-ref?access_num=11742045&link_type=MED&atom=%2Febnurs%2F5%2F3%2F82.atom [4]: /lookup/external-ref?access_num=000172656100001&link_type=ISI

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.074
GPT teacher head0.335
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations1
Published2002
Admission routes2
Has abstractyes

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