Session: 634. Myeloproliferative Syndromes: Clinical and Epidemiological: Poster I
Hematology Disease Topics & Pathways:
Research, Translational Research, MPN, Chronic Myeloid Malignancies, Diseases, Myeloid Malignancies, Technology and Procedures, Pathology
Aims&Methods: This retrospective, single-center study aimed to validate the RCOs and explore its clinical, genetic and prognostic correlates in a large cohort of clinically and molecularly annotated PMF pts diagnosed according to 2022 ICC criteria. The RCOs was assessed by two independent experienced histopathologists (U.G, R.S.).
Results: The study included 222 pts with a diagnosis of PMF: 121 (55%) prefibrotic PMF (pre-PMF), 101 (45%) overt PMF. Median age was 66 years (range, 18-91), 127 (57%) were male.
BM histological analysis according to the RCO algorithm provided the following results: MF-0 n=20 (9%), MF-1 n=102 (46%), MF-2 n=47 (21%), and MF-3 n=53 (24%); Co-0 n=130 (59%), Co-1 n=33 (15%), Co-2 n=31 (14%), and Co-3 n=28 (13%); Ost-0 n=146 (66%), Ost-1 n=45 (20%), Ost-2 n=18 (8%), and Ost-3 n=13 (6%). Next, we looked at the distribution of the Co and Ost variables according to MF grade and PMF diagnosis. Overall, morphological features evolved harmonically, with pre-PMF showing the less severe stromal changes and higher reticulin fibrosis being associated with the highest values of Co and Ost.
Computation of the RCOs returned the following results: RCOs 0 n=20 (9%), RCOs 1 n=94 (42%), RCOs 2 n=15 (7%), RCOs 3 n=19 (9%), RCOs 4 n=9 (4%), RCOs 5 n=16 (7%), RCOs 6 n=13 (6%), RCOs 7 n=17 (8%), RCOs 8 n=11 (5%), and RCOs 9 n=8 (4%). Median RCOs for pts with pre- and overt PMF was 1 (range, 0-2) and 5 (range, 2-9), respectively.
We investigated the correlations of RCOs with clinical and molecular variables. Higher RCOs was associated with overt PMF (median, 5 vs 1, P<.0001), male gender (median, 3 vs 1, P=.0005), lower hemoglobin (Pearson's r, -0.5, P<.0001), lower platelets (Pearson's r, -0.4, P<.0001), higher blasts (Pearson's r, 0.4, P<.0001), higher LDH (Pearson's r, 0.5, P<.0001), and higher prevalence of splenomegaly (median, 3 vs 1, P<.0001) and constitutional symptoms (median, 5 vs 1, P=.0004). As to molecular variables, a higher RCOs was associated with abnormal karyotype (median, 3 vs 1, P=.0003), absent JAK2 mut (median, 2 vs 1, P=.0224) but higher JAK2 allele burden in JAK2-mut pts (Pearson's r, 0.3, P<.0006), triple negativity (median, 5 vs 1, P=.0223), EZH2 mut (median, 6 vs 1, P=.0033), ASXL1 mut (median, 6 vs 1, P<.0001), KRAS mut (median, 8 vs 1, P=.0059), and HMR status (i.e., ≥1 mut in ASXL1, EZH2, IDH1/2, SRSF2) (median, 5 vs 1, P<.0001).
Median overall survival (OS) was 96 months (95% CI 81-134). In univariate Cox regression analysis, RCOs directly correlated with risk of death (HR 3.1, 95% CI 1.5-6.3, P=.0023). MF and Co variables correlated with OS (respectively: HR 4.0, 95% CI 1.8-8.6, P=.0003; HR 2.7, 95% CI 1.5-5.0, P=.0008), unlike Ost. ROC analysis with death as endpoint confirmed 5 as the optimal cut-off value (Histopathol 2017;71:89). Pts with RCOs >5 (n=65 overt PMF) had significantly worst OS compared to pts with RCOs <5 (n=121/36 pre-/overt PMF), with median values of 64 vs 134 months (HR 2.3, 95% CI 1.4-3.6, P=.0004) (Fig. 1A). Considering only overt PMF pts, ROC analysis confirmed 5 as the more accurate cut-off value (univariate survival analysis: HR 2.1, 95% CI 1.1-4.2, P=.0257).
We finally computed the MIPSS70 by replacing the original BM fibrosis grade ≥2 variable with the dichotomous RCOs5 (>/<5) in 177 (80%) pts with full molecular information, and calculated the C-index, Brier score, and time-dependent area under the curve (AUC) (Fig. 1B). The highest values for performance and accuracy in predicting death were achieved by the RCOs5-integrated MIPSS70 at 12, 36, and 48 months.
Conclusions: Our findings confirm the clinical and prognostic consistency of RCOs, supporting the importance of a comprehensive and accurate evaluation of BM stromal changes in PMF. Integration of RCOs within the MIPSS70 might improve the predictive performance of the model.
Disclosures: Guglielmelli: Novartis: Other: Other member of advisory board, speaker at meeting, Speakers Bureau; Abbvie: Other: Other member of advisory board, speaker at meeting, Speakers Bureau; GSK: Speakers Bureau. Vannucchi: Incyte: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; GSK: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Blueprint: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AOP: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Imago BioSciences, Inc., a subsidiary of Merck & Co., Inc., Rahway, NJ, USA: Research Funding.
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