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Record W4407568940 · doi:10.1186/s12909-025-06761-3

Implementation of a student-run initiative to facilitate multidisciplinary cancer care in Pakistan: the Tumor Board Establishment Facilitation Forum

2025· article· en· W4407568940 on OpenAlexaff
Muhammad Abdul Rehman, Urooba Jawwad Rao, Erfa Tahir, Unaiza Naeem, Maheen Qamar, Nowal Hussain, Nimrata Kumari, Ahmed Nadeem Abbası, Agha Muhammad Hammad Khan

Bibliographic record

VenueBMC Medical Education · 2025
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsMcGill University
Fundersnot available
KeywordsMultidisciplinary approachFacilitationMedical educationMedicinePsychologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The lack of a multidisciplinary approach to the management of cancer patients in most parts of Pakistan is a long-standing and major concern. To overcome this disparity, we started a student-run initiative to facilitate the establishment of multidisciplinary tumor boards (MTBs) in oncology, titled "Tumor Board Establishment Facilitation Forum (TEFF)". The objectives of this study were to evaluate the clinical and academic impact of TEFF on cancer care for patients and student education, respectively. METHODS: The formation of TEFF was based on the Theory of Change model. We conducted a needs assessment based on existing literature, physical evaluation of wards, and consultation with senior academic faculty members. The logic model was refined through multiple meetings between stakeholders. All engagements of TEFF described in this manuscript are limited to the Dow Medical College and its affiliated tertiary care hospital, Dr. Ruth K. M. Pfau Civil Hospital in Karachi, Pakistan. To gauge TEFF's impact, we used administrative data generated between October 2021 to March 2024 to evaluate predefined outcomes (number of MTBs, cases, educational interventions, and research). RESULTS: The organizational structure comprised of 6 specialized departments: Communications, Operations, Media, Integrated Development, Research and Records, and Finance. We conducted 18 educational sessions for medical students about career guidance, research, cancer awareness; and 4 cancer awareness campaigns. TEFF facilitated the formation of 4 MTBs: breast, head and neck, gynecology, and pediatrics. Across these, 105 cases were discussed in 50 meetings. TEFF provided leadership opportunities, allowed familiarization with oncology, raised awareness of challenges associated with cancer care, allowed networking, and inculcated research-related skills and educational value through its MTBs. CONCLUSION: Medical students can contribute significantly to clinical care at the undergraduate level. For countries/regions struggling to provide multidisciplinary cancer care, TEFF's model serves as a blueprint for a viable solution.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.079
GPT teacher head0.474
Teacher spread0.395 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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