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Record W4307238576 · doi:10.3390/curroncol29110632

Sintilimab-Induced Diabetic Ketoacidosis in a Patient with Radiation and Multichemorefractory Penile Cancer: A Case Report and Literature Review

2022· review· en· W4307238576 on OpenAlexvenueno aff
Chuan Lv, Can Wu, Yan Zhang, Wendong Li, Xuesong Wang, Liang Li

Bibliographic record

VenueCurrent Oncology · 2022
Typereview
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsnot available
FundersNatural Science Foundation of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsMedicinePenectomyDiabetic ketoacidosisPenile cancerRadiation therapyDocetaxelCancerOncologySurgeryInternal medicineInsulin

Abstract

fetched live from OpenAlex

Penile squamous cell carcinoma (PSCC) is a rare disease. The treatment options for advanced penile cancer are often limited, and the prognosis remains poor. We reported a 52-year-old male recurrent and metastatic PSCC patient with high PD-L1 expression (90%) and TMB (14.4 muts/Mb). He had undergone penectomy, bilateral inguinal lymph node dissection, and excision of the abdominal wall mass. Despite cisplatin-based concurrent chemoradiotherapy and sequential chemotherapy with docetaxel plus cisplatin then being carried out, the carcinoma still progressed. The patient then obtained progression-free survival with continuous sintilimab, although he experienced the new onset of ICI-induced diabetes after 24 cycles of sintilimab and required sustained insulin treatment. He had negative type 1 diabetes-associated autoantibodies and the susceptible HLA genotype DR3-DQ2 haplotype. This is the first patient with radiation and multichemorefractory PSCC who has obtained the remarkable anti-tumor effect of partial regression exceeding 32 months during continuous sintilimab and anlotinib treatment.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.102
GPT teacher head0.447
Teacher spread0.345 · 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 designCase report
Domainnot available
GenreReview

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

Citations2
Published2022
Admission routes1
Has abstractyes

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