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Record W1830195387 · doi:10.1002/bjs.9192_1

Consensus statement on the multidisciplinary management of patients with recurrent and primary rectal cancer beyond total mesorectal excision planes

2013· article· en· W1830195387 on OpenAlexaff
Simak Ali, Anthony Antoniou, John Beynon, Aneel Bhangu, Pradeep Bose, Kirsten Boyle, Graham Branagan, Gina Brown, David Burling, George J. Chang, Susan K. Clark, Patrick Colquhoun, Christopher H. Crane, Ara Darzi, Prajnan Das, Johannes H.W. de Wilt, Conor P. Delaney, Anant Desai, Mark Davies, David Dietz, Eric J. Dozois, M. J. Duff, Adam Dziki, J.E.F. Fitzgerald, Frank Frizelle, Bruce George, Mark George, Panagiotis Georgiou, Rob Glynne‐Jones, Robert Goldin, Arun Gupta, Deena Harji, Dean Harris, M. Hawkins, Alexander G. Heriot, Torbjörn Holm, Roel Hompes, Lee Jeys, John T. Jenkins, Ravi P. Kiran, Cherry Koh, Søren Laurberg, Wai Lun Law, A. Sender Liberman, Michelle Marshall, D. Ray McArthur, Alex H. Mirnezami, Brendan Moran, Neil Mortenson, Eddie Myers, R. John Nicholls, P. R. O’Connell, Sarah O’Dwyer, Alex Oliver, Arvind Pallan, Prashant Patel, Uday Patel, Kelvin Ramsey, P. Rasmussen, Carole Richard, H.J.T. Rutten, P. M. Sagar, David Sebag‐Montefiore, Michael J. Solomon, Luca Stocchi, Carol J. Swallow, Diana Tait, Emile Tan, Paris Tekkis, Nicholas van As, T. Vuong, Theo Wiggers, Malcolm Wilson, Desmond C. Winter, Christopher Woodhouse

Bibliographic record

VenueBritish journal of surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsJewish General HospitalPrincess Margaret Cancer CentreMcGill UniversityCentre Hospitalier de l’Université de MontréalMcGill University Health CentreMount Sinai HospitalWestern University
FundersImperial College LondonNational Institute for Health and Care ResearchCancer Research UK
KeywordsMedicineTotal mesorectal excisionDelphi methodColorectal cancerDelphiReferralMultidisciplinary approachConsensus conferenceVotingGeneral surgerySurgeryMedical physicsFamily medicineCancerInternal medicineStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: The management of primary rectal cancer beyond total mesorectal excision planes (PRC-bTME) and recurrent rectal cancer (RRC) is challenging. There is global variation in standards and no guidelines exist. To achieve cure most patients require extended, multivisceral, exenterative surgery, beyond conventional total mesorectal excision planes. The aim of the Beyond TME Group was to achieve consensus on the definitions and principles of management, and to identify areas of research priority. METHODS: Delphi methodology was used to achieve consensus. The Group consisted of invited experts from surgery, radiology, oncology and pathology. The process included two international dedicated discussion conferences, formal feedback, three rounds of editing and two rounds of anonymized web-based voting. Consensus was achieved with more than 80 per cent agreement; less than 80 per cent agreement indicated low consensus. During conferences held in September 2011 and March 2012, open discussion took place on areas in which there is a low level of consensus. RESULTS: The final consensus document included 51 voted statements, making recommendations on ten key areas of PRC-bTME and RRC. Consensus agreement was achieved on the recommendations of 49 statements, with 34 achieving consensus in over 95 per cent. The lowest level of consensus obtained was 76 per cent. There was clear identification of the need for referral to a specialist multidisciplinary team for diagnosis, assessment and further management. CONCLUSION: The consensus process has provided guidance for the management of patients with PRC-bTME or RRC, taking into account global variations in surgical techniques and technology. It has further identified areas of research priority.

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)0.191
metaresearch head score (Gemma)0.184
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.191
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1910.184
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0040.003
Science and technology studies0.0050.004
Scholarly communication0.0040.003
Open science0.0070.010
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0040.003

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 head0.020
GPT teacher head0.255
Teacher spread0.234 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations259
Published2013
Admission routes1
Has abstractyes

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