ABSTRACT
BACKGROUND: In myelofibrosis (MF), new model scores are continuously proposed to improve the ability to better identify patients with the worst outcomes. In this context, the Artificial Intelligence Prognostic Scoring System for Myelofibrosis (AIPSS-MF), and the Response to Ruxolitinib after 6 months (RR6) during the ruxolitinib (RUX) treatment, could play a pivotal role in stratifying these patients. AIMS: We aimed to validate AIPSS-MF in patients with MF who started RUX treatment, compared to the standard prognostic scores at the diagnosis and the RR6 scores after 6 months of treatment. METHODS AND RESULTS: At diagnosis, the AIPSS-MF performs better than the widely used IPSS for primary myelofibrosis (C-index 0.636 vs. 0.596) and MYSEC-PM for secondary (C-index 0.616 vs. 0.593). During RUX treatment, we confirmed the leading role of RR6 in predicting an inadequate response by these patients to JAKi therapy compared to AIPSS-MF (0.682 vs. 0.571). CONCLUSION: The new AIPSS-MF prognostic score confirms that it can adequately stratify this subgroup of patients already at diagnosis better than standard models, laying the foundations for new prognostic models developed tailored to the patient based on artificial intelligence.
Subject(s)
Primary Myelofibrosis , Humans , Prognosis , Primary Myelofibrosis/diagnosis , Primary Myelofibrosis/drug therapy , Primary Myelofibrosis/complications , Artificial Intelligence , Machine LearningABSTRACT
The wide use of ruxolitinib, approved for treating primary and secondary myelofibrosis (MF), has revolutionized the landscape of these diseases. This molecule can reduce spleen volume and constitutional symptoms, guaranteeing patients a better quality of life and survival or even a valid bridge to bone marrow transplantation. Despite a rapid response within the first 3 to 6 months of treatment, some patients fail to achieve a significant benefit or lose early response. After ruxolitinib failure, new drugs are available to provide an additional therapeutic option for these patients. However, the correct timing point for deciding on a therapy shift is still an open challenge. Recently, a clinical prognostic score named RR6 (Response to Ruxolitinib after 6 months) was proposed to determine survival after 6 months of treatment with ruxolitinib in patients affected by MF. We applied this model to a cohort of consecutive patients treated at our center to validate the results obtained in terms of median overall survival (mOS): for the low-risk class, mOS was not reached (as in the training cohort); for the intermediate-risk, mOS was 52 months (95% CI 39-106); for the high-risk, it was 33 (95% 8.5-59). Moreover, in addition to the other studies present in the literature, we evaluated how the new RR6 score could better identify primary MF patients at high risk, with a slight or no agreement compared to DIPSS, contrary to what occurs in secondary MF. Thus, we were able to confirm the predictive power of the RR6 model in our series, which might be of help in guiding future therapeutic choices.
ABSTRACT
Fourteen novel vanin-1 inhibitors coded OMP-# were designed from RR6 and successfully synthesized by a nucleophilic addition-elimination reaction of the pantetheinic acid-derived Weinreb amide as a key step under Barbier conditions. The synthesized OMP compounds exhibited inhibitory activity against human serum vanin-1 in vitro. Among the synthesized compounds, OMP-7, which possesses a trifluoromethoxy group at the para-position on the phenyl ring, exhibited the most potent activity, approximately 20 times that of the mother compound RR6. OMP-7 was further subjected to an in vivo assay using a normal hamster. More potent activity was observed than that of RR6 against both serum and renal vanin-1. The activity lasted for 4 h after injection against serum vanin-1 and 1 h after injection against renal vanin-1, whereas RR6 did not show the desired activity.