MétaCan
Menu
Back to cohort
Record W4406946439 · doi:10.1093/ofid/ofae631.850

P-653. Epidemiology of <i>Streptococcus pneumoniae</i> serotypes using serotype specific urinary antigen (SSUAD) in cancer patients

2025· article· en· W4406946439 on OpenAlexaboutno aff
Melvilí Cintrón, Varshini Gali, Krupa Jani, Anna Kaltsas, Mini Kamboj, Susan K. Seo, Genovefa A. Papanicolaou, Yeon Joo Lee

Bibliographic record

VenueOpen Forum Infectious Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSerotypeStreptococcus pneumoniaeEpidemiologyAntigenVirologyUrinary systemMicrobiologyImmunologyInternal medicineBiologyAntibiotics

Abstract

fetched live from OpenAlex

Abstract Background Cancer patients have a 2.4-fold higher risk of dying from pneumonia compared to the general population. Streptococcus pneumoniae is one of the most common etiologies of community-acquired pneumonia. Serotype specific information of nonbacteremic pneumococcal pneumonia in oncology settings is limited. Thus, we described the frequency of S. pneumoniae serotypes detected by a serotype-specific urinary antigen (SSUAD) assay in cancer patients.Table 1.Clinical characteristics of adult oncology patients tested with SSUAD Methods This was an interim analysis of a prospective observational study from 1/1/2023 - 1/31/2024. Cancer patients aged ≥18 years at MSKCC, inpatient or outpatient, with a Streptococcus urine antigen test (SUA) ordered at clinician’s discretion for diagnostic work-up of pneumonia were included. SUA was performed in-house using the BinaxNOW™, a lateral flow immunochromatographic test that detects C-polysaccharide cell wall protein common to all S. pneumoniae serotypes. Batched urine samples were tested using SSUAD, which detects the 15 pneumococcal serotypes (1, 3, 4, 5, 6A, 6B, 7F, 9V, 14, 18C, 19A, 19F, 22F, 23F, 33F) covered by 15-valent pneumococcal conjugate vaccine (PCV15) at Q2 laboratories (Quebec, Canada).Table 2.Patients with S. pneumoniae infections, positive SUA, and positive SSUAD by pneumococcal vaccine status Results Of 1324 patients, 780 (58.9%) were ≥65 years old and 486 (36.7%) had hematologic malignancies (Table 1). Thirteen patients had positive SUA (1 positive SSUAD and 12 negative SSUAD). Thirty patients had a positive SSUAD and only 1 of these patients also had a positive SUA (Figure 1). In 9 patients who had S. pneumoniae recovered from a culture (sputum [N=2] or blood [N=7]), SUA was only positive in 2 of the blood culture positive patients and none by SSUAD. Among the 30 patients with positive SSUAD, pneumococcus serotype 7F was most common with 26.3%, followed by 3 (17.5%), 5 (7.0%), 18C (7.0%), and 33F (7.0%); 12 (40%) had ≥2 serotypes detected (Figure 2). Pneumococcal vaccination status of the 49 patients with corresponding SUA and SSUAD results are summarized in Table 2. Conclusion Among cancer patients with positive SSUAD detecting PCV15 serotypes, 7F (26.3%), 3 (17.5%), 5 (7.0%), 18C (7.0%), and 33F (7.0%) predominated. More studies are needed to further understand the sero-epidemiology of circulating pneumococcal serotypes in this patient population. Disclosures Melvili Cintron, PhD, D(ABMM), Copan Diagnostics: Grant/Research Support|Merck & Co: Grant/Research Support|Roche Diagnostics: Advisor/Consultant Susan K. Seo, MD, Merck: Grant/Research Support Genovefa Papanicolaou, MD, AlloVir: Advisor/Consultant|AlloVir: Data safety monitoring committee|Merck: Advisor/Consultant|Merck: Grant/Research Support|Merck: Investigator|Symbio: Advisor/Consultant Yeon Joo Lee, MD, MPH, AiCuris: institutional research support for clinical trials|Karius: institutional research support for clinical trials|Merck: Grant/Research Support|Scynexis: institutional research support for clinical trials

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.367
Teacher spread0.332 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOpen Forum Infectious DiseasesSame topicNeutropenia and Cancer InfectionsFrench-language works237,207