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Record W2912062763 · doi:10.1182/blood-2018-99-109740

3,023 Mayo Clinic Patients with Myeloproliferative Neoplasms: Risk-Stratified Comparison of Survival and Outcomes Data Among Disease Subgroups

2018· article· en· W2912062763 on OpenAlexaff
Natasha Szuber, Mythri Mudireddy, Maura Nicolosi, Domenico Penna, Rangit Vallapureddy, Terra L. Lasho, Christy M. Finke, Kebede H. Begna, Michelle A. Elliott, C. Christopher Hook, Alexandra P. Wolanskyj, Mrinal M. Patnaik, Curtis A. Hanson, Rhett P. Ketterling, Shireen Sirhan, Animesh Pardanani, Naseema Gangat, Lambert Busque, Ayalew Tefferi

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-RosemontJewish General Hospital
Fundersnot available
KeywordsMedicineMyelofibrosisPolycythemia veraEssential thrombocythemiaInternal medicinePopulationInternational Prognostic Scoring SystemMyelodysplastic syndromesBone marrow

Abstract

fetched live from OpenAlex

Abstract Background: While several population-based studies have reported on adverse outcomes and life expectancy in myeloproliferative neoplasms (MPN) (JCO. 2015;33:2288; AJH. 1999;61:10; Leukemia. 2013;27:1874; JCO. 2012;30:2995), large-scale studies reporting mature data have been rare and important questions remain unanswered. The current study documents the Mayo Clinic (MC) decades-long experience with over 3,000 consecutive MPN patients including polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF) with the majority of patients followed until death. Herein, we provide mature, and importantly, risk-stratified survival data and disease complication estimates. Methods: Study patients were recruited from MC, Rochester, MN, USA between 10/27/1967 and 12/29/2017. All MPN diagnoses and documentation of fibrotic/leukemic transformations were in accordance with the 2016 World Health Organization criteria (Blood. 2016;127:2391). Clinical and laboratory data were abstracted from medical records. Risk-stratification used conventional risk models considering age, leukocytes, and venous thrombosis for PV (Leukemia. 2013;27:1874), international prognostic score for ET (Blood. 2012;120:1197), and dynamic international prognostic scoring system for PMF (Blood. 2010;115:1703). Statistical analyses were based on parameters obtained at the time of referral to MC which, in the majority of cases, coincided with or was within 1 year of diagnosis. All patients were followed from diagnosis until death or date of last follow-up/contact. Recipients of allogeneic stem cell transplants were censored at the time of transplant. Standard statistical methods and time-to-event curves prepared using the Kaplan-Meier method were used to compare MPN subgroups. Survival data for low-risk ET/PV were compared with age- and sex-matched controls from Olmstead County, MN, USA. JMP® Pro 13.0.0 software (SAS Institute, Cary, NC, USA) was used for all analyses. Results: 3,023 consecutive patients (median age 62 years, range 18-96; 51% males) were considered, including 89% diagnosed within the year: 665 PV, 1076 ET and 1282 PMF. Conventional risk stratification in 2925 evaluable patients revealed low, intermediate, and high-risk status in 26%, 29%, and 45% of PV and 30%, 42%, and 28% of ET patients, respectively, while PMF cases were attributed low (14%), intermediate-1 (38%) -2 (40%) and high (8%) risk (Table 1). After a median follow-up of 8.2 years for PV (range 0-39), 9.9 for ET (range 0-47), and 3.2 for PMF (range 0-31), 1631 (54%) deaths, 183 (6%) leukemic transformations, 244 (14%) fibrotic progressions, and 516 (17%) thrombotic events were recorded (Table 1). Median overall survival (OS) was 18 years for ET, 15 for PV and 4.4 for PMF (p<0.05 for all inter-group comparisons) (Figure 1A). Leukemia-free survival was similar for ET and PV (p=0.22) and significantly worse for PMF (p<0.001) (Figure 1B). PV, compared to ET, was associated with higher risk of fibrotic progression (p<0.001) (Figure 1C). Thrombosis risk after diagnosis was highest in PV and lowest in PMF (p=0.002 for PV vs ET; 0.56 for ET vs PMF; and 0.001 for PV vs PMF) (Figure 1D). Following risk stratification, median OS in low-risk ET (28 years) and low-risk PV (27 years) were superimposed (p=0.89) (Figure 2). Similarly, intermediate or high-risk PV and ET patients had comparable OS within each risk strata (p=0.23 and 0.11, respectively). Low-risk PMF survival was analogous to that of intermediate-risk PV (p=0.06). All other risk-stratified categories disclosed significantly different inter- and intra-group survival patterns (p<0.001) (Figure 2). Despite their categorization as favorable-risk disease, both low-risk ET and low-risk PV displayed excess mortality relative to age- and sex-matched controls with median survival of 26.7 and 28.1 years respectively, compared to the expected 37.5 and 39.2 years (p<0.001) (Figure 3). Conclusions: The current study provides large-scale and uniquely mature survival and outcomes data in MPN and highlights MPN subgroup risk categorization as cardinal in appraising disease natural history. Interestingly, OS was only marginally better in ET, compared to PV, while the latter clearly displayed a higher risk of thrombosis and fibrotic progression. Moreover, data disclosed shortened life expectancy relative to matched controls even in MPN with favorable risk attribution. Disclosures Busque: BMS: Consultancy; Novartis: Consultancy; Pfizer: Consultancy; Paladin: Consultancy.

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)0.001
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.316
Teacher spread0.282 · 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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Citations33
Published2018
Admission routes1
Has abstractyes

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