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Record W3216627495 · doi:10.1182/blood-2021-147626

Investigating Erythrocytosis: Changing Practice Patterns in the Era of Molecular Diagnostics

2021· article· en· W3216627495 on OpenAlexaffabout
Benjamin Chin‐Yee, Maxim Matyashin, Pratibha Bhai, Ian Cheong, Alan Stuart, Eri Kawata, Sean Cuninghame, Michael A. Levy, Alejandro Lazo‐Langner, Hanxin Lin, Ian Chin‐Yee, Bekim Sadiković, Cyrus C. Hsia

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineMolecular diagnosticsPolycythemia veraClinical PracticeInternal medicineDiagnostic testRetrospective cohort studyPediatricsFamily medicineBioinformaticsBiology

Abstract

fetched live from OpenAlex

Abstract Background: Since the identification of JAK2 mutations in polycythemia vera (PV) in 2005 (Kralovics et al., NEJM 2005), molecular testing of JAK2 in patients with erythrocytosis has become part of routine clinical practice. We hypothesized that changes in the World Health Organization (WHO) diagnostic criteria for PV in 2016, which lowered the hemoglobin threshold to >165 g/L for men and >160 g/L for women, may have resulted in increased molecular testing. This study examines changing patterns of utilization of molecular diagnostics in patients referred for erythrocytosis at a tertiary care center. Methods: We examined all patients with erythrocytosis who underwent JAK2 testing, which included testing for JAK2 V617F with PCR between 2015 and 2017, and JAK2 V617F and exon 12 mutations with Next-Generation Sequencing (NGS) between 2018 and 2020 at London Health Sciences Centre in Ontario, Canada. We performed a retrospective chart review to extract laboratory and clinical data, including information on medical comorbidities and medications, with a focus on known secondary causes of erythrocytosis. Results: A total of 668 patients with erythrocytosis underwent JAK2 testing at our institution between August 1, 2015 and December 31, 2020. There was an overall increase in testing over the five-year study period, with a decline in the positive detection rate: 8/29 (28%) in 2015, 15/94 (16%) in 2016, 15/100 (15%) in 2017, 19/136 (14%) in 2018, 17/162 (10%) in 2019, and 14/147 (10%) in 2020 (Figure 1). The average hemoglobin levels in patients with erythrocytosis who underwent testing remained similar across all years (range 170-173 g/L for women, 179-181 g/L for men). In our cohort, there was a high proportion of patients with known or suspected secondary causes of erythrocytosis who underwent molecular testing. Between 2018 and 2020, 324/445 (73%) of patients who underwent molecular testing had either chronic obstructive pulmonary disease, obstructive sleep apnea, other hypoxic lung disease, smoking history, erythropoietin-secreting tumor, or potential drug-induced erythrocytosis. Specifically, we observed an increase in proportion of patients who underwent molecular testing on sodium-glucose cotransporter-2 (SGLT-2) inhibitors, a known secondary cause of erythrocytosis, with 15/136 (11%) in 2018, 17/162 (10%) in 2019, and 25/147 (17%) in 2020. In contrast, the proportion of patients on testosterone was relatively constant at 15/136 (11%) in 2018, 11/162 (6.8%) in 2019, and 11/147 (7.5%) in 2020. Conclusion: This study revealed that a high proportion of patients with known or suspected secondary causes of erythrocytosis underwent JAK2 testing, resulting in increase in molecular testing over time and a decline in positive detection rate. In particular, we observed a number of patients on SGLT-2 inhibitors who had investigation, suggesting that this class of medications may be an underrecognized cause of drug-induced erythrocytosis (Chin-Yee et al., CMAJ 2020). Our findings underscore the importance of careful medical history and medication review to support more judicious use of molecular testing. Similarity in average hemoglobin levels across the five-year study period suggests that other factors, such as increased availability of 'routine' molecular testing, rather than changes in the WHO diagnostic criteria may explain increases in JAK2 testing. Our study indicates a need to develop an effective clinical prediction rule for JAK2 positivity to better risk stratify patients with suspected PV based on clinical and laboratory parameters to optimize utilization of molecular diagnostics. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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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)0.003
metaresearch head score (Gemma)0.013
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.282
Teacher spread0.264 · 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".

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Citations2
Published2021
Admission routes2
Has abstractyes

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