Clinicopathological Features, Clinical Efficacy on 101 Cases of Rectal Gastrointestinal Stromal Tumors, and the Significance of Neoadjuvant Therapy

Abstract Objective: To investigate the clinicopathological features, clinical efficacy on 101 cases of rectal gastrointestinal stromal tumors (GISTs), and the significance of Imatinib Mesylate (IM) neoadjuvant therapy.Methods: The clinicopathological features, treatment methods, peri-operative data, and prognosis of the patients were summarized and analyzed on 101 patients with rectal GISTs, who received treatment in the Gastrointestinal Department of West China Hospital of SichuanUniversity and the Affiliated Hospital of Guizhou Medical University from August 2002 toNovember 2020 in China. Results: A total of 101 patients, including 64 males and 37 females, were aged from 22 to 79 years (55.4±12.2 years). Among 70 patients with direct surgery, which included 8 very low risk cases, 10 low risk cases, 7 intermediate risk cases, and 45 high risk cases. Cox regression analysis showed that post-operative IM adjuvant treatment improved disease-free survival (DFS) and overall survival (OS) of 52 intermediate and high risk patients. Among the 31 patients who received neoadjuvant therapy, the objective response rate (ORR) was 83.9% (26/31), and the disease control rate (DCR) reached 96.8% (30/31). Diameter subgroup analysis: (1) Among the 36 patients with a diameter ≤ 5 cm, two patients received IM neoadjuvant therapy, while 34 patients received direct surgery. Both univariate and Cox regression analysis did not find that neoadjuvant therapy affects DFS and OS. (2) Among the 65 patients of diameter >5 cm, 29 received IM neoadjuvant therapy and 36 received direct surgery. Patients who underwent neoadjuvant therapy had less blood loss (P=0.022) , shorter post-operative hospital stay (P=0.001), increased anal preservation proportion (93.1% VS72.2% , P=0.031), decreased enterostomy proportion (10.3% VS 33.3%, P=0.037) than those who underwent direct surgery. Cox regression analysis suggested that neoadjuvant therapy and post-operative IM adjuvant therapy improved DFS. Conclusion: Rectal GISTs is relatively rare and is a highly malignant tumor, post-operative oral IM therapy can improve DFS and OS of intermediate and high risk patients. In patients with rectal GISTs with diameter > 5 cm, IM neoadjuvant therapy can improve the anal preservation proportion , preserve the structure and function of the organs, reduce enterostomy proportion, and improve prognosis.

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Clinicopathological features, clinical efficacy on 101 cases of rectal gastrointestinal stromal tumors, and the significance of neoadjuvant therapy

BMC Surgery ◽

10.1186/s12893-021-01397-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Hongxin Yang ◽

Chaoyong Shen ◽

Xiaonan Yin ◽

Zhaolun Cai ◽

Qian Wang ◽

...

Keyword(s):

Regression Analysis ◽

High Risk ◽

Neoadjuvant Therapy ◽

Cox Regression ◽

Retention Rate ◽

Clinicopathological Features ◽

Cox Regression Analysis ◽

Stromal Tumors ◽

Risk Patients ◽

Rectal Gists

Abstract Objective To investigate the clinicopathological features and clinical efficacy among 101 cases of rectal gastrointestinal stromal tumors (GISTs) and to investigate the significance of imatinib mesylate (IM) neoadjuvant therapy. Methods The clinicopathological features, treatment methods, perioperative data, and prognosis of the patients were summarized and analysed in 101 patients with rectal GISTs who received treatment in the Gastrointestinal Surgery of West China Hospital of Sichuan University and the Affiliated Hospital of Guizhou Medical University from August 2002 to November 2020 in China. Results A total of 101 patients, including 64 males and 37 females, were aged from 22 to 79 years (55.4 ± 12.2 years). Among the 70 patients who underwent direct surgery, 8 were very low risk cases, 10 were low risk cases, 7 were intermediate risk cases, and 45 were high risk cases. Cox regression analysis showed that postoperative IM adjuvant treatment improved the disease-free survival (DFS) and overall survival (OS) of 52 intermediate and high risk patients. Among the 31 patients who received neoadjuvant therapy, the objective response rate (ORR) was 83.9% (26/31), and the disease control rate (DCR) reached 96.8% (30/31). Subgroup analysis was also conducted based on the tumour diameter. (1) Among the 36 patients with a diameter ≤ 5 cm, two patients received IM neoadjuvant therapy, while 34 patients received direct surgery. Neither univariate nor Cox regression analysis found that neoadjuvant therapy affected DFS and OS. (2) Among the 65 patients with a diameter > 5 cm, 29 received IM neoadjuvant therapy, and 36 received direct surgery. Patients who underwent neoadjuvant therapy had less blood loss (P = 0.022), shorter postoperative hospital stay (P = 0.001), increased anal retention rate (93.1% vs. 72.2%, P = 0.031), and decreased enterostomy rate (10.3% vs. 33.3%, P = 0.037) than those who underwent direct surgery. Cox regression analysis suggested that neoadjuvant therapy and postoperative IM adjuvant therapy improved DFS. Conclusion Rectal GISTs are relatively rare and highly malignant tumors. Postoperative oral IM therapy can improve the DFS and OS of intermediate and high risk patients. In patients with rectal GISTs with diameters > 5 cm, IM neoadjuvant therapy can improve anal retention rate, preserve the structure and function of the organs, reduce enterostomy rate, and improve prognosis.

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Development of prognosis model for colon cancer based on autophagy-related genes

World Journal of Surgical Oncology ◽

10.1186/s12957-020-02061-w ◽

2020 ◽

Vol 18 (1) ◽

Author(s):

Xu Wang ◽

Yuanmin Xu ◽

Ting Li ◽

Bo Chen ◽

Wenqi Yang

Keyword(s):

Colon Cancer ◽

Regression Analysis ◽

High Risk ◽

Cancer Patients ◽

Risk Score ◽

Cox Regression ◽

Patient Survival ◽

Expression Profiles ◽

Cox Regression Analysis ◽

Risk Patients

Abstract Background Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied. Methods Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis. Results Twenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians. Conclusion The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

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Development of prognosis model for colon cancer based on autophagy-related genes

10.21203/rs.3.rs-40420/v2 ◽

2020 ◽

Author(s):

Xu Wang ◽

Yuanmin Xu ◽

Ting Li ◽

Bo Chen ◽

Wenqi Yang

Keyword(s):

Colon Cancer ◽

Regression Analysis ◽

High Risk ◽

Cancer Patients ◽

Risk Score ◽

Cox Regression ◽

Patient Survival ◽

Expression Profiles ◽

Cox Regression Analysis ◽

Risk Patients

Abstract Background: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.Methods: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazards models were used to investigate the association between ARG expression profiles and patient prognosis.Results: 20 ARGs were significantly associated with overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p<0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 3- and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.Conclusion: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

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Prognosis and Characterization of Immune Microenvironment in Acute Myeloid Leukemia Through Identification of an Autophagy-Related Signature

Frontiers in Immunology ◽

10.3389/fimmu.2021.695865 ◽

2021 ◽

Vol 12 ◽

Author(s):

Denggang Fu ◽

Biyu Zhang ◽

Shiyong Wu ◽

Yinghua Zhang ◽

Jingwu Xie ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Regression Analysis ◽

High Risk ◽

Signaling Pathways ◽

Myeloid Leukemia ◽

Cox Regression ◽

Cox Regression Analysis ◽

Prognostic Predictor ◽

Risk Patients ◽

Acute Myeloid

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has an unfavorable outcome and a high rate of relapse. Autophagy plays a vital role in the development of and therapeutic responses to leukemia. This study identifies a potential autophagy-related signature to monitor the prognoses of patients of AML. Transcriptomic profiles of AML patients (GSE37642) with the relevant clinical information were downloaded from Gene Expression Omnibus (GEO) as the training set while TCGA-AML and GSE12417 were used as validation cohorts. Univariate regression analyses and multivariate stepwise Cox regression analysis were respectively applied to identify the autophagy-related signature. The univariate Cox regression analysis identified 32 autophagy-related genes (ARGs) that were significantly associated with the overall survival (OS) of the patients, and were mainly rich in signaling pathways for autophagy, p53, AMPK, and TNF. A prognostic signature that comprised eight ARGs (BAG3, CALCOCO2, CAMKK2, CANX, DAPK1, P4HB, TSC2, and ULK1) and had good predictive capacity was established by LASSO–Cox stepwise regression analysis. High-risk patients were found to have significantly shorter OS than patients in low-risk group. The signature can be used as an independent prognostic predictor after adjusting for clinicopathological parameters, and was validated on two external AML sets. Differentially expressed genes analyzed in two groups were involved in inflammatory and immune signaling pathways. An analysis of tumor-infiltrating immune cells confirmed that high-risk patients had a strong immunosuppressive microenvironment. Potential druggable OS-related ARGs were then investigated through protein–drug interactions. This study provides a systematic analysis of ARGs and develops an OS-related prognostic predictor for AML patients. Further work is needed to verify its clinical utility and identify the underlying molecular mechanisms in AML.

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Development of prognosis model for colon cancer based on autophagy-related genes

10.21203/rs.3.rs-40420/v3 ◽

2020 ◽

Author(s):

Xu Wang ◽

Yuanmin Xu ◽

Ting Li ◽

Bo Chen ◽

Wenqi Yang

Keyword(s):

Colon Cancer ◽

Regression Analysis ◽

High Risk ◽

Cancer Patients ◽

Risk Score ◽

Cox Regression ◽

Patient Survival ◽

Expression Profiles ◽

Cox Regression Analysis ◽

Risk Patients

Abstract Background: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.Methods: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazards models were used to investigate the association between ARG expression profiles and patient prognosis.Results: 20 ARGs were significantly associated with overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3- and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.Conclusion: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

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Development of prognosis model for colon cancer based on autophagy-related genes

10.21203/rs.3.rs-40420/v1 ◽

2020 ◽

Author(s):

Xu Wang ◽

Yuanmin Xu ◽

Ting Li ◽

Bo Chen ◽

Wenqi Yang

Keyword(s):

Colon Cancer ◽

Regression Analysis ◽

High Risk ◽

Cancer Patients ◽

Risk Score ◽

Cox Regression ◽

Patient Survival ◽

Expression Profiles ◽

Cox Regression Analysis ◽

Risk Patients

Abstract Background: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.Methods: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and AGRs related to overall patient survival were identified. Cox proportional-hazards models were used to investigate the association between ARG expression profiles and patient prognosis.Results: 20 ARGs were significantly associated with overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p<0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 3- and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.Conclusion: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

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A Risk Signature of Nine Autophagy-Related Genes Associated With Immune Microenvironment and Clinical Prognosis in Wilms Tumor

10.21203/rs.3.rs-892534/v1 ◽

2021 ◽

Author(s):

Shaopei Ye ◽

Wenbin Tang ◽

Ke Huang

Keyword(s):

Regression Analysis ◽

High Risk ◽

Risk Score ◽

Cox Regression ◽

Wilms Tumor ◽

Risk Group ◽

High Risk Group ◽

Differentially Expressed ◽

Clinical Prognosis ◽

Cox Regression Analysis

Abstract Background: Autophagy is a biological process to eliminate dysfunctional organelles, aggregates or even long-lived proteins. . Nevertheless, the potential function and prognostic values of autophagy in Wilms Tumor (WT) are complex and remain to be clarifed. Therefore, we proposed to systematically examine the roles of autophagy-associated genes (ARGs) in WT.Methods: Here, we obtained differentially expressed autophagy-related genes (ARGs) between healthy and Wilms tumor from Therapeutically Applicable Research To Generate Effective Treatments(TARGET) and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology. Then univariate COX regression analysis and multivariate COX regression analysis were performed to acquire nine autophagy genes related to WT patients’ survival. According to the risk score, the patients were divided into high-risk and low-risk groups. The Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis.Results: Eighteen DEARGs were identifed, and nine ARGs were fnally utilized to establish the FAGs based signature in the TCGA cohort. we found that patients in the high-risk group were associated with mutations in TP53. We further conducted CIBERSORT analysis, and found that the infiltration of Macrophage M1 was increased in the high-risk group. Finally, the expression levels of crucial ARGs were verifed by the experiment, which were consistent with our bioinformatics analysis.Conclusions: we emphasized the clinical significance of autophagy in WT, established a prediction system based on autophagy, and identified a promising therapeutic target of autophagy for WT.

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A Tumor Progression Related 7-Gene Signature Indicates Prognosis and Tumor Immune Characteristics of Gastric Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.690129 ◽

2021 ◽

Vol 11 ◽

Author(s):

Fen Liu ◽

Zongcheng Yang ◽

Lixin Zheng ◽

Wei Shao ◽

Xiujie Cui ◽

...

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Cancer Progression ◽

Risk Score ◽

Risk Model ◽

Cox Regression ◽

Hub Genes ◽

Cox Regression Analysis ◽

High Risk Patients ◽

Risk Patients

BackgroundGastric cancer is a common gastrointestinal malignancy. Since it is often diagnosed in the advanced stage, its mortality rate is high. Traditional therapies (such as continuous chemotherapy) are not satisfactory for advanced gastric cancer, but immunotherapy has shown great therapeutic potential. Gastric cancer has high molecular and phenotypic heterogeneity. New strategies for accurate prognostic evaluation and patient selection for immunotherapy are urgently needed.MethodsWeighted gene coexpression network analysis (WGCNA) was used to identify hub genes related to gastric cancer progression. Based on the hub genes, the samples were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between the subtypes, a gastric cancer risk model was constructed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The differences in prognosis, clinical features, tumor microenvironment (TME) components and immune characteristics were compared between subtypes and risk groups, and the connectivity map (CMap) database was applied to identify potential treatments for high-risk patients.ResultsWGCNA and screening revealed nine hub genes closely related to gastric cancer progression. Unsupervised clustering according to hub gene expression grouped gastric cancer patients into two subtypes related to disease progression, and these patients showed significant differences in prognoses, TME immune and stromal scores, and suppressive immune checkpoint expression. Based on the different expression patterns between the subtypes, we constructed a gastric cancer risk model and divided patients into a high-risk group and a low-risk group based on the risk score. High-risk patients had a poorer prognosis, higher TME immune/stromal scores, higher inhibitory immune checkpoint expression, and more immune characteristics suitable for immunotherapy. Multivariate Cox regression analysis including the age, stage and risk score indicated that the risk score can be used as an independent prognostic factor for gastric cancer. On the basis of the risk score, we constructed a nomogram that relatively accurately predicts gastric cancer patient prognoses and screened potential drugs for high-risk patients.ConclusionsOur results suggest that the 7-gene signature related to tumor progression could predict the clinical prognosis and tumor immune characteristics of gastric cancer.

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Ten-year overall and prostate cancer (PCa)-specific mortality in high-risk patients after high-dose-rate brachytherapy combined with external beam radiation therapy (HDR-BT/EBRT) compared with EBRT alone.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.5059 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 5059-5059

Author(s):

Trude Baastad Wedde ◽

Sophie Fosså ◽

Sigmund Brabrand ◽

Stein Kaasa ◽

Kjell Magne Russnes ◽

...

Keyword(s):

Regression Analysis ◽

High Risk ◽

Gleason Score ◽

Dose Escalation ◽

Cox Regression ◽

Seminal Vesicles ◽

External Beam Radiation ◽

Beam Radiation ◽

Cox Regression Analysis ◽

Specific Mortality

5059 Background: The effect of dose-escalation with HDR-BT boost for high-risk PCa is not known. The objective is to compare 10-year PCa-specific mortality (PCSM) and overall mortality (OM) in non-metastatic patients treated with HDR-BT/EBRT (2004-2010) to EBRT alone (historical RCT, SPCG-7, 1996-2003). Methods: HDR-BT boosts (10 Gy x 2) were given 2 weeks apart followed by 50 Gy conformal EBRT (2 Gy x 25) to the prostate and seminal vesicles (assuming alpha/beta ratio of 3, EQD2 = 102 Gy). The HDR-BT/EBRT group (N:325) received Androgen Deprivation Therapy (ADT) for a total of 2 years. Patients in the control group (N:296) received 70 Gy (2Gy x 35) to the prostate and seminal vesicles with lifelong Anti-Androgen Treatment (AA). cT1-cT2 vs cT3 tumours and Gleason score 6-7 vs 8-10 were analysed. For each treatment group PCSM and OM were established by Kaplan-Meier (KM) analyses, and inter-treatment differences were tested by the logrank tests. Cox regression analysis evaluated the significance of available pre-treatment variables. Significance level p < 0.05. Results: In both groups the median age was 66 years. Median follow-up was 104 (range 13-120) and 120 (range 3-120) months for the HDR-BT/EBRT and EBRT groups respectively. KM plots revealed an 1.8% risk of PCSM in the HDR-BT/EBRT patient group and an 8.4% risk in the EBRT cohort (p = 0.001). For OM, the figures were 12.3% in the HDR-BT/EBRT group compared to 23.3% in the EBRT group (p = 0.014). In the Cox regression analysis, treatment (HR = 3.9, CI95% 1.8-8.3) and Gleason score (HR = 3.2, CI95% 1.8-5.9) were significantly associated with PCSM whilst T-stage, age and PSA levels were not. Treatment (HR = 1.7, CI95% = 1.1-2.6) was the only factor significantly associated with OM. Conclusions: In men with high-risk PCa dose-escalation with HDR-BT/EBRT compared to EBRT alone resulted in a significantly decreased risk of 10-year PCSM and OM despite shorter length of hormonal therapy. PCSM was significantly influenced by both Gleason score and type of treatment, whereas treatment remained the only significant covariate for OM.

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Risk Factors for Leukemic Transformation Among 1,306 Patients with Primary Myelofibrosis: Mutations Predict Early Events

Blood ◽

10.1182/blood-2018-99-109895 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 3044-3044

Author(s):

Rangit Reddy Vallapureddy ◽

Mythri Mudireddy ◽

Natasha Szuber ◽

Domenico Penna ◽

Maura Nicolosi ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

High Risk ◽

Cox Regression ◽

Primary Myelofibrosis ◽

Idh1 Mutation ◽

Severe Anemia ◽

Cox Regression Analysis ◽

Version 2.0

Abstract Background: Current prognostic models in primary myelofibrosis (PMF) target overall survival (OS) and utilize MIPSS70 (mutation-enhanced international prognostic scoring system for transplant-age patients), MIPSS70+ version 2.0 (karyotype-enhanced MIPSS70) and GIPSS (genetically-inspired prognostic scoring system, which is based on mutations and karyotype) (JCO 2018;36:310; JCO doi: 10.1200/JCO.2018.78.9867; Leukemia. 2018;doi:10.1038/s41375-018-0107). In the current study, we used logistic regression statistics to identify risk factors for leukemic transformation (LT) within 5 years of diagnosis/referral (i.e. early events) and also performed Cox regression analysis of overall leukemia-free survival (LFS). Methods : Study patients were recruited from the Mayo Clinic, Rochester, MN, USA. Diagnoses of LT and chronic phase PMF were confirmed by both clinical and bone marrow examinations, in line with the 2016 World Health Organization criteria (Blood. 2016;127:2391); specifically, LT required presence of ≥20% blasts in the peripheral blood (PB) or bone marrow (BM) (Blood 2016;127:2391). Statistical analyses considered clinical and laboratory data collected at the time of initial PMF diagnosis or Mayo Clinic referral point. Logistic regression statistics was used to identify predictors of LT at 5 years from initial diagnosis/referral; in the particular method, patients with documented LT within 5 years were "uncensored" while those followed up for at least 5 years, without developing LT, were "censored"; the analysis excluded patients without LT and not followed for at least 5 years. In addition, Cox regression analysis was performed to identify risk factors for overall LFS. The JMP® Pro 13.0.0 software from SAS Institute, Cary, NC, USA, was used for all calculations. Results: 1,306 patients with PMF (median age 65 years; 63% males) were included in the current study; MIPSS70+ version 2.0 risk distribution was 20% very high risk, 41% high risk, 19% intermediate risk, 16% low risk and 4% very low risk. 149 (11%) patients were documented to experience LT, and compared to the remaining patients (n=1157), they were more likely to be males (p=0.02) and mutated for ASXL1 (p=0.01), SRSF2 (0.001) and IDH1 (0.02) and present with higher risk MIPSS70+ version 2.0 (p=0.02). Multivariable logistic regression identified the following as predictors of LT in the first 5 years of disease: IDH1 mutation (odds ratio; OR 78.4), very high risk (VHR) karyotype (OR 57.6), ASXL1 mutation (OR 15.1), age >70 years (OR 13.3), SRSF2 mutation (OR 8.5), male sex (OR 6.9), PB blasts ≥3% (OR 5.4), presence of moderate or severe anemia, adjusted for sex (OR 3.6) and constitutional symptoms (OR 3.1). On Cox regression analysis, the following were associated with inferior LFS: IDH1 mutation (HR 4.3), PB blasts ≥3% (HR 3.3), SRSF2 mutation (HR 3.0), age >70 years (HR 2.1), ASXL1 mutation (HR 2.0) and presence of moderate or severe anemia, adjusted for sex (HR 1.9). Subsequently, HR-based risk point allocation resulted in highly discriminating LT predictive model with HR (95% CI) of 39.4 (10.8-114) for high risk and 4.1 (2.4-7.3) for intermediate risk (Figure 1). Conclusions: The current study identifies IDH1 mutation as a main predictor of LT in PMF. Our study also implicates SRSF2 and ASXL1 mutations and VHR karyotype as other genetic markers of early LT. Other independent contributors of early LT and inferior LFS, overall, included PB blasts ≥3%, moderate to severe anemia and older age. We provide LT prediction model, based on these variables, with leukemia risk ranging from 8% to 57%. Disclosures No relevant conflicts of interest to declare.

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