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Record W1879213842 · doi:10.1186/s13643-015-0099-y

Comparison of physical interventions, behavioral interventions, natural health products, and pharmacologics to manage hot flashes in patients with breast or prostate cancer: protocol for a systematic review incorporating network meta-analyses

2015· review· en· W1879213842 on OpenAlexafffundabout
Brian Hutton, Fatemeh Yazdi, Louise Bordeleau, Scott C. Morgan, Chris Cameron, Salmaan Kanji, Dean Fergusson, Andrea C. Tricco, Sharon E. Straus, Becky Skidmore, Mona Hersi, Misty Pratt, Sasha Mazzarello, Melissa Brouwers, David Moher, Mark Clemons

Bibliographic record

VenueSystematic Reviews · 2015
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsOttawa Public HealthSt. Michael's HospitalMcMaster UniversityOttawa HospitalUniversity of Ottawa
FundersNational Center for Complementary and Integrative HealthCanadian Institutes of Health ResearchNational Center for Complementary and Alternative MedicineNational Institutes of Health
KeywordsMedicineProstate cancerPsychological interventionProtocol (science)Breast cancerMeta-analysisSystematic reviewAlternative medicineNatural historyCancerMEDLINEPhysical therapyInternal medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Breast and prostate cancers are the most commonly diagnosed non-dermatologic malignancies in Canada. Agents including endocrine therapies (e.g., aromatase inhibitors, gonadotrophin-releasing hormone analogs, anti-androgens, tamoxifen) and chemotherapy have improved survival for both conditions. As endocrine manipulation is a mainstay of treatment, it is not surprising that hot flashes are a common and troublesome adverse effect. Hot flashes can cause chills, night sweats, anxiety, and insomnia, lessening patients' quality of life. These symptoms impact treatment adherence, worsening prognosis. While short-term estrogen replacement therapy is frequently used to manage hot flashes in healthy menopausal women, its use is contraindicated in breast cancer. Similarly, testosterone replacement therapy is contraindicated in prostate cancer. It is therefore not surprising that non-hormonal pharmacological treatments (anti-depressants, anti-epilectics, anti-hypertensives), physical/behavioral treatments (e.g., acupuncture, yoga/exercise, relaxation techniques, cognitive behavioral therapy), and natural health products (e.g., black cohosh, flax, vitamin E, ginseng) have been studied for control of hot flashes. There is a need to identify which interventions minimize the frequency and severity of hot flashes and their impact on quality of life. This systematic review and network meta-analysis of randomized studies will synthesize available evidence addressing this knowledge gap. METHODS/DESIGN: An electronic search of Medline, Embase, AMED, PsycINFO, and the Cochrane Register of Controlled Trials has been designed by an information specialist and peer reviewed by a second information specialist. Study selection and data collection will be performed by two reviewers independently. Risk of bias assessments will be completed using the Cochrane Risk of Bias Scale. Outcomes of interest will include validated measures of hot flash severity, hot flash frequency, quality of life, and harms. Bayesian network meta-analyses will be performed where judged appropriate based on review of clinical and methodologic features of included studies. DISCUSSION: Our review will include a broad range of interventions that patients with breast and prostate cancer have attempted to use to manage hot flashes. Our work will establish the extent of evidence underlying these interventions and will employ an inclusive approach to analysis to inform comparisons between them. Our findings will be shared with Cancer Care Ontario for consideration in the development of guidance related to supportive care in these patients. PROSPERO: CRD42015024286.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0260.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.560
GPT teacher head0.610
Teacher spread0.050 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreProtocol

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

Citations21
Published2015
Admission routes3
Has abstractyes

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