MétaCan
Menu
← Back to cohort
Record W4411846646 · doi:10.3899/jrheum.2025-0314.30

Description of Immune Checkpoint Inhibitor Associated Sicca-Like Syndrome from the Canadian Research Group of Rheumatology in Immuno-Oncology Database: A Case Series

2025· article· en· W4411846646 on OpenAlexaffvenueabout
Brianna Greenwood, Shahin Jamal, Marie Hudson, Janet Roberts, Aurore Fifi‐Mah, Megan E. Himmel, Janet Pope, Alexandra Saltman, Lourdes Gonzales Arreola, May Y. Choi, Faiza Khokhar, Alexandra Ladouceur, Carrie Ye

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsMcGill UniversityMcMaster UniversitySt Joseph's Health CentreUniversity of British ColumbiaUniversity of TorontoWestern UniversityJewish General HospitalDalhousie UniversityResearch CanadaUniversity of CalgaryArthritis Research Centre of CanadaUniversity of Alberta
Fundersnot available
KeywordsMedicineRheumatologyInternal medicineSicca syndromeOncologyDermatologyDisease

Abstract

fetched live from OpenAlex

Objectives Immune checkpoint inhibitors (ICIs) are a revolutionary cancer treatment that block inhibition of T cells, promoting immune-mediated clearance of malignancies. Decreased regulation of T cells can have many off-target effects, including the development of xerostomia and xeropthalmia, also called ICI-sicca syndrome.[1] ICI-sicca syndrome appears to be pathophysiologically distinct from Sjögren’s syndrome,[2] though predictors of sicca development in ICI patients have not been well characterized. The development of Sicca Syndrome can seriously impact on patient quality of life, causing lifelong toxicity to oral and ocular health. Reporting of sicca symptoms in randomized controlled trials is not currently standard. Little is known about the clinical presentation, response to treatment, and prognosis of those who develop ICI-sicca syndrome. Our objective was to characterize sicca symptom manifestation, management, and outcomes in patients treated with ICIs using the Canadian Research Group of Rheumatology in Immuno-Oncology (CanRIO) prospective and retrospective cohort databases. Methods We identified 40 cases of Sicca symptoms after exposure to ICI treatment in the CanRIO database. In this study, we describe the characteristics of these cases of ICI-sicca syndrome including cancer and ICI treatment history, Sicca symptom history, other immune-related adverse events (irAEs), medical management of irAEs, and investigations undertaken. Results Of the 40 patients identified with sicca-like symptoms, 19 (47.5%) were treated with anti-PD-1 monotherapy, 15 (37.5%) with combination anti-PD-1 and anti-CTLA-4, and 6 (15%) with anti-PD-L1 monotherapy. Thirty-five records contained information on the sicca symptom CTCAE grade; of these, 15 patients (42.9%) were recorded with grade 1 sicca symptoms, 14 (40%) grade 2, and 6 (17.1%) grade 3. Only 3 patients had previously experienced sicca-like symptoms, and 32 presented with additional irAEs. Serologies showed a distinctly different pattern from Sjögren’s syndrome, with 37.9% positive for ANA, 13.8% positive for rheumatoid factor, 34.6% positive for anti-Ro, and 4.2% positive for anti-La. Of this cohort, 72.7% had management initiated specifically for sicca symptoms, including topical management, pilocarpine, systemic glucocorticoid, and ICI pause or cessation. Fourteen of 16 patients reported partial or complete resolution of their Sicca symptoms with treatment. Conclusion To date, this is the largest case series on sicca treatments and outcomes in ICI-treated patients worldwide. ICI-induced sicca, in contrast to traditional Sjögren’s syndrome, appears to be highly responsive to immunosuppressive treatments. This work characterized a wide range of treatment modalities and may assist those involved in ICI-treated patients’ care to initiate therapy and reduce the risk of serious complications of sicca syndrome. [1.] Harris J. Oral Dis 2022;28:2083-2092. [2.] Warner B. Oncologist 2019;24:1259-69.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.318
Teacher spread0.281 · 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
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 routes3
Has abstractyes

Explore more

Same venueThe Journal of Rheumatology→Same topicCancer Immunotherapy and Biomarkers→French-language works237,207→