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Record W4387267320 · doi:10.7759/cureus.46366

Curative Intent Radiation for Anal Cancer in Pelvic Kidney Transplant: A Case Report With an Eight-Year Follow-Up

2023· article· en· W4387267320 on OpenAlexaff
Alexandre Riopel, Lucy Ward, Nikhilesh Patil

Bibliographic record

VenueCureus · 2023
Typearticle
Languageen
FieldMedicine
TopicColorectal and Anal Carcinomas
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineAnal cancerRadiation therapyUrologySurgeryKidneyRadiologyCancerInternal medicine

Abstract

fetched live from OpenAlex

The incidence of malignancies seen after solid organ transplant is increasing, and oncologists are seeing more patients with transplanted organs. In this case report, we present how pelvic radiotherapy can be safely administered in a patient with a transplanted kidney by conducting a comprehensive chart review and analyzing the dosimetry in the radiotherapy planning software Eclipse. A 52-year-old female patient received a kidney transplant in 2002 and was diagnosed 11 years later with a cT3 N0 M0 squamous cell carcinoma of the anal canal. She was offered radical radiation therapy with 45 Gy in 25 fractions using a volumetric modulated arc therapy plan to the pelvic lymph nodes and tumor followed by a 9-Gy boost to the anal tumor alone using a three-dimensional conformal radiation therapy plan with concurrent 5-fluorouracil/mitomycin chemotherapy for a total dose of 54 Gy. The right external iliac and inguinal lymph nodes coverage was compromised to decrease the solitary pelvic kidney dose in addition to creating a 1-cm planning risk volume around the kidney and using half-beam blocks. Her pelvic kidney only received a mean dose of 6.68 Gy. Eight years later, the patient continues to be cancer-free, as evident with a recent sigmoidoscopy in 2021 and a physical examination in 2022. Her creatinine started to rise one year post-treatment, but age of the transplanted kidney is likely the cause of kidney failure.

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 score0.216
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.310
Teacher spread0.278 · 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
Published2023
Admission routes1
Has abstractyes

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