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Record W4252044922 · doi:10.2196/13566

Receipt of Curative Resection or Palliative Care for Hepatopancreaticobiliary Tumours (RICOCHET): Protocol for a Nationwide Collaborative Observational Study

2019· article· en· W4252044922 on OpenAlexvenueno aff

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyMedicineReceiptProtocol (science)Palliative careMedical emergencyNursingComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: There are variations in the management of patients with suspected pancreatic and periampullary cancers and/or malignant biliary obstruction. These differences may be due to a number of organizational, institutional, and patient factors that could affect outcomes for those with curable or incurable disease. The Receipt of Curative Resection or Palliative Care for Hepatopancreaticobiliary Tumours (RICOCHET) study will be the first to provide a snapshot of investigative pathways across the United Kingdom to reflect the real-world practice in these patients. The RICOCHET study is contemporary to new national and international clinical guidance and can potentially inform future local and national strategic planning to optimize care for patients with suspected hepatopancreaticobiliary (HPB) malignancies. OBJECTIVE: The aim of this study is to define national variation in the investigative and management pathways of patients with suspected HPB malignancies and to determine the effect of these variations on patient outcomes. METHODS: The RICOCHET study is a nationwide, multicenter, prospective study. It is led by trainees through collaboration between surgical and medical specialties. Patients with suspected pancreatic cancer, other periampullary cancer, or extrahepatic cholangiocarcinoma presenting to hospitals in the United Kingdom will be identified over 90 days. Each case will be followed up for 90 days to collect data on the mode of presentation, investigations, interventions, use of local and specialist multidisciplinary team meetings, and transfer of care between hub and spoke sites. Furthermore, the study will define dates and intervals between key points in the patient pathway. RESULTS: The RICOCHET study results and analyses will be subject to peer review by presenting them at international cross-specialty conferences and by submitting them for publication in open-access journals. Moreover, our findings will be presented to patient groups and sponsoring charities (eg, Pancreatic Cancer UK), who in turn will disseminate key findings to the primary beneficiaries of the results: the patients. The RICOCHET study was funded in September 2017. Data collection started in April 2018 and the planned end date for data upload is spring 2019. Data analysis will take place in the summer of 2019 and the first results are expected to be published in late 2019 or early 2020. CONCLUSIONS: The RICOCHET study is a multidisciplinary, prospective, observational study that aims to highlight variability in practice and to determine whether these affect the outcomes of patients with HPB malignancies. This is a trainee-led initiative that utilizes a novel design to achieve full coverage of the differences in diagnostic and management pathways. The RICOCHET study may provide evidence to develop a more standardized approach to managing patients with suspected HPB malignancy. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13566.

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)0.059
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.059
Threshold uncertainty score0.314

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.040
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0040.006
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0240.006

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 head0.445
GPT teacher head0.614
Teacher spread0.169 · 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 designObservational
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

Citations12
Published2019
Admission routes1
Has abstractyes

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