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Record W6968628207 · doi:10.5281/zenodo.4005019

Effect of regional anaesthesia only versus general anaesthesia on cancer recurrence rate: A systematic review and meta-analysis with trial sequential analysis

2020· article· en· W6968628207 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyCancerRandomized controlled trialIncidence (geometry)General anaesthesiaInclusion and exclusion criteriaCancer recurrenceClinical trial

Abstract

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Introduction There is growing evidence on the influence of general anaesthesia (GA) in promoting the proliferation of cancer cells. RA comprised of epidural, spinal and nerve block, which can attenuate surgical stress response by reducing catecholamine levels and minimizing immunosuppression. The benefits of regional anaesthesia (RA) on cancer recurrence rate in cancer surgery remains unclear in the literature. Objectives To examine the effect of RA-only on the incidence of post-operative cancer recurrence rate in cancer resection surgery. Methods This review was conducted and reported in adherence to the Cochrane Handbook and PRISMA statement 2015. The protocol was registered and published on a public database, PROSPERO (CRD42020163780). Databases: MEDLINE, EMBASE and CENTRAL (its inception until April 2020) Inclusion criteria: Randomized clinical trials, observational studies (cohort or case-control) Exclusion criteria: Case reports, case series and editorials Primary outcome: Incidence of cancer recurrence rate Secondary outcomes: Overall survival rate, time to cancer recurrence and cancer-related mortality All the included observational studies were assessed for risk of bias using the Newcastle-Ottawa Scale. Results The titles and abstracts of 4477 non-duplicate articles were screened, of which 44 articles were retrieved. After applying inclusion and exclusion criteria, 10 observational studies with a total of 9708 patients (4567 GA vs 5141 RA-only) were included for qualitative and quantitative meta-analysis. In comparison to GA, RA-only was not significantly associated with a lower cancer recurrence rate in cancer resection surgery (p=0.95, certainty of evidence=very low, Fig 1). However, the trial sequential analysis for cancer recurrence rate was inconclusive (Fig 2). Our analysis demonstrated no significant difference between the RA-only and GA groups in the overall survival rate (odds ratio 1.51, 95% CI 0.65 to 3.51, p=0.34, certainty of evidence=very low), time to cancer recurrence (mean difference 1.45 months, 95% CI -8.69 to 11.59, p=0.78, certainty of evidence=very low) and cancer-related mortality (odds ratio 1.79, 95% CI 0.57 to 5.62, p=0.32, certainty of evidence=very low). Discussion First meta-analysis of the effect of RA-only versus routine care GA in cancer resection surgery. At present, only 22.2% of required information size (16031 patients) available to detect significance difference of 20% reduction in incidence of cancer recurrence. Substantial heterogeneity non-RCT, inadequate sample size True effect of GA-only may be skewed by many small sample size observational studies with conflicting results and substantial heterogeneity. Confounding factors: types of GA (TIVA/ volatile), amount of opioids use, types of cancer surgery. Conclusions Given the low level of evidence and underpowered trial sequential analysis, our review neither support nor oppose that the use of RA-only was associated with lower incidence of cancer recurrence rate than GA in cancer resection surgery.

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)0.022
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.051
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0270.050
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.316
Teacher spread0.242 · 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 designMeta-analysis
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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