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

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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Risk factors for severe anemia requiring red blood cell transfusions in lymphoma patients receiving chemotherapy

Journal of Clinical Oncology ◽

10.1200/jco.2007.25.18_suppl.19537 ◽

2007 ◽

Vol 25 (18_suppl) ◽

pp. 19537-19537

Author(s):

X. Zhou ◽

S. R. Teegala ◽

A. Huen ◽

Y. Ji ◽

L. E. Fayad ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

High Risk ◽

Significant Risk ◽

Baseline Risk ◽

Severe Anemia ◽

Nodal Involvement ◽

Initial Regimen ◽

Number Of Cycles

19537 Background: Anemia is a frequent complication in lymphoma pts receiving chemotherapy (CT). However, the exact incidence of anemia with the current regimens and risk factors for severe anemia are not well established. Methods: A retrospective cohort study was conducted to determine the incidence of anemia requiring transfusions (Tx). Medical records of all newly referred lymphoma pts (n=1046) in 2003 were reviewed. Logistic regression analysis was performed to identify the clinical and laboratory features correlated with anemia in lymphoma pts during initial regimen received. Results: 425 pts who received ≥ 1 cycle of treatment at MDACC were included in this analysis. Median age was 57 (range 17–87) with 262 (62%) newly diagnosed. Most common first regimens were CHOP (29%), Hyper-CVAD ± Ara-c-MTX (23%), and ABVD (8%) (± rituxan- R).The total number of cycles 1638 (median 3, range, 1–10). The incidence of anemia requiring PRBC Tx was 32 % (136/425) of pts and 14% (231/1638) of cycles (median cycle-2 for Tx). The incidence of PRBC Tx ranged from 8% to 17 % in each cycle. The incidence of PRBC Tx among most common regimens were Hyper-CVAD/ Ara-c/MTX 69 %( 66/95), CHOP 23% (29/125), and ABVD 6% (2/34). In the univariate regression analysis, CT, stage, extranodal/BM involvement, histology, Hb, Ca, β2M, LDH, WBC/lymphocyte counts, were significantly associated with the Txs. Using multivariate logistic regression, baseline Hb (< 12 g/dL vs. ≥ 12 g/dL: OR 2.659, 95% CI 1.670 to 4.232, p< 0.0001), extra nodal involvement (± : OR 2.578, 95% CI 1.609 to 4.133, p<0.0001), and CT (high vs low risk: OR 3.889, 95% CI 2.446 to 6.183, p<0.0001) were the most important baseline risk factors for PRBC Txs. Conclusions: The incidence of anemia in this population is high in early cycles. Baseline pt characteristics including Hb (<12g/dL), extra nodal involvement, and high risk CT were found to be significant risk factors predictive for anemia and Txs. These findings could be useful to identify high risk pts for consideration of prophylaxis with erythropoietic agents for prevention of anemia. No significant financial relationships to disclose.

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Risk Factors for the Morbidity and Prognosis of Lung Metastases in Newly Diagnosed Ovarian Carcinoma: A Large Population-based Study

10.21203/rs.3.rs-737681/v1 ◽

2021 ◽

Author(s):

Shuning Ding ◽

Kaibo Guo ◽

Linqin Wu ◽

Dongxu Li ◽

Peipei Wang ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Ovarian Carcinoma ◽

Cox Regression ◽

Lung Metastases ◽

Population Based ◽

Ca 125 ◽

Newly Diagnosed ◽

Cox Regression Analysis

Abstract Background: To evaluate the risk factors for the morbidity and prognosis of lung metastases (LM) in patients with newly diagnosed ovarian carcinoma (OC). Methods: Based on the Surveillance, Epidemiology, and End Results (SEER) dataset, OC patients from 2010 and 2016 were retrospectively analyzed. Risk factors for the morbidity of LM in OC patients and their survival were assessed by logistic regression analysis and Kaplan-Meier and Gray method, respectively. Cox regression analysis was performed to identify risk factors for the prognosis of OC patients with LM, and their prognostic potentials were further validated by two established nomograms.Results: There are 27,123 eligible OC patients were enrolled in the study, with the morbidity of LM at 5.61% (1,521/27,123). Logistic regression models illustrated that T3 stage [odds ratio (OR)=2.74, 95%CI=2.09-3.66, P<0.01], advanced N stage (OR=1.86, 95%CI=1.62-2.14, P<0.01), and the prevalence of bone metastasis (OR=3.78, 95%CI=2.79-5.11, P<0.01), brain metastasis (OR=4.67, 95%CI=2.50-8.63, P<0.01) and liver metastasis (OR=3.60, 95%CI=3.14-4.12, P<0.01) were all significantly correlated with the morbidity of LM in OC patients. Median survival for OC patients with LM was 11 months (interquartile range, 3 to 25 months). Cox regression analyses illustrated over 80 years of age [hazard ratio (HR)=2.52, 95%CI=2.33-2.72, P<0.01] and positive expression of cancer antigen 125 (CA-125, HR=1.63, 95%CI=1.47-1.82, P<0.01) were significantly correlated with the high mortality of LM, while chemotherapy (HR=0.62, 95%CI=0.59-0.65, P<0.01) was significantly correlated with the low mortality. Two nomograms were established to examine the concordance index (C-index), calibration curves, the area under the curve (AUC), decision curve analyses (DCAs) and clinical impact curves (CICs), which validated the prognostic potentials of identified risk factors in OC patients with LM. Conclusion: The population-based cohort study provides references for guiding clinical screening and individualized treatment of OC patients with LM.

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Abstract 2308: Conventional Aortic Valve Replacement in Very Elderly Patients

Circulation ◽

10.1161/circ.118.suppl_18.s_703-c ◽

2008 ◽

Vol 118 (suppl_18) ◽

Author(s):

Gerald M Lawrie ◽

Elizabeth A Earle ◽

Nan R Earle

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

High Risk ◽

Cox Regression ◽

Bacterial Endocarditis ◽

Very Elderly ◽

Conventional Surgery ◽

Perioperative Mortality ◽

Cox Regression Analysis ◽

Valve Size

Suboptimal early and late results of percutaneous AVR have been justified by its use in patients claimed to be at high risk for conventional surgery, particularly the very elderly. We performed an analysis to identify which risk factors in conventional AVR patients are most predictive of mortality and to quantify those risk factors in order to provide a realistic baseline for comparison. We analyzed the outcome of surgery in 1168 patients operated on over a 31 year period on one service. Of those patients, 50 suffered perioperative mortality. Of those, 54% (27/50) were male vs. 62% (699/1118) who did not suffer perioperative mortality and 32% (16/50) vs 22% (242/1118) were >76 yrs old; 21% (9/43) vs. 25% (241/982) had diabetes, and 9.3% (9/43) vs. 5.5 (54/982) had bacterial endocarditis (all p=NS); 22% (11/50) vs. 11% (122/1118) had a prior MI (p=0.0152); 26% (13/50) vs 11% (118/1118) had a prior CAB (p=0.0007); 46% (23/49) vs 29% (322/1118) had a concurrent CAB (p=0.0063); mean EF of 44.50±18.26 vs. 53.33±13.90 (p<0.0001); and mean replacement valve size of 20.69±2.14 vs. 21.75±2.46 (p=0.0031). Logistic regression analysis identified prior CAB (odds ratio (OR) 1.65. p<0.01), concurrent CAB (OR 1.63, p<0.01), bacterial endocarditis (OR 1.85, p<0.05) and replacement valve size (OR 0.81, p<0.01 – larger size is protective) as predictors of perioperative mortality. Age was not a predictor of perioperative mortality. Cox regression analysis for factors predictive of overall mortality identified age (relative risk (RR)1.046, 4.6%/yr, p<0.0001) preop EF (RR 0.982, decrease risk of 1.8%/1% increase EF, p<0.0001), diabetes (RR 1.254, p=0.0031, 25% increase risk with diabetes), and replacement valve size (RR 0.889, p=0.0004, 11.1% decreased risk/mm valve size.) These data suggest that even in high-risk patients, perioperative mortality is relatively low and is not predicted by age alone; therefore conventional surgery should be seriously considered in almost all patients. Age is only one of several risk factors which should be evaluated.

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A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma

Technology in Cancer Research & Treatment ◽

10.1177/15330338211027912 ◽

2021 ◽

Vol 20 ◽

pp. 153303382110279

Author(s):

Qinping Guo ◽

Yinquan Wang ◽

Jie An ◽

Siben Wang ◽

Xiushan Dong ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Cox Regression ◽

Signet Ring Cell Carcinoma ◽

Signet Ring Cell ◽

Training Set ◽

Cox Regression Analysis ◽

Signet Ring ◽

Ring Cell ◽

Independent Risk Factors

Background: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and validation sets. Multivariate Cox regression analyses screened for OS and CSS independent risk factors and nomograms were constructed. Results: A total of 7,149 eligible GSRC patients were identified, including 4,766 in the training set and 2,383 in the validation set. Multivariate Cox regression analysis showed that gender, marital status, race, AJCC stage, TNM stage, surgery and chemotherapy were independent risk factors for both OS and CSS. Based on the results of the multivariate Cox regression analysis, prognostic nomograms were constructed for OS and CSS. In the training set, the C-index was 0.754 (95% CI = 0.746-0.762) for the OS nomogram and 0.762 (95% CI: 0.753-0.771) for the CSS nomogram. In the internal validation, the C-index for the OS nomogram was 0.758 (95% CI: 0.746-0.770), while the C-index for the CSS nomogram was 0.762 (95% CI: 0.749-0.775). Compared with TNM stage and SEER stage, the nomogram had better predictive ability. In addition, the calibration curves also showed good consistency between the predicted and actual 3-year and 5-year OS and CSS. Conclusion: The nomogram can effectively predict OS and CSS in patients with GSRC, which may help clinicians to personalize prognostic assessments and clinical decisions.

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NLRP3 is a Novel Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma and Skin Cutaneous Melanoma

10.21203/rs.3.rs-880002/v1 ◽

2021 ◽

Author(s):

Chenxi Yuan ◽

Qingwei Wang ◽

Xueting Dai ◽

Yipeng Song ◽

Jinming Yu

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Lung Adenocarcinoma ◽

Immune Cells ◽

Cutaneous Melanoma ◽

Cox Regression ◽

Cox Regression Analysis ◽

Potential Biomarker ◽

The Impact ◽

Nlrp3 Expression

Abstract Background: Lung adenocarcinoma (LUAD) and skin cutaneous melanoma (SKCM) are common tumors around the world. However, the prognosis in advanced patients is poor. Because NLRP3 was not extensively studied in cancers, so that we aimed to identify the impact of NLRP3 on LUAD and SKCM through bioinformatics analyses. Methods: TCGA and TIMER database were utilized in this study. We compared the expression of NLRP3 in different cancers and evaluated its influence on survival of LUAD and SKCM patients. The correlations between clinical information and NLRP3 expression were analyzed using logistic regression. Clinicopathologic characteristics associated with overall survival in were analyzed by Cox regression. In addition, we explored the correlation between NLRP3 and immune infiltrates. GSEA and co-expressed gene with NLRP3 were also done in this study. Results: NLRP3 expressed disparately in tumor tissues and normal tissues. Cox regression analysis indicated that up-regulated NLRP3 was an independent prognostic factor for good prognosis in LUAD and SKCM. Logistic regression analysis showed increased NLRP3 expression was significantly correlated with favorable clinicopathologic parameters such as no lymph node invasion and no distant metastasis. Specifically, a positive correlation between increased NLRP3 expression and immune infiltrating level of various immune cells was observed. Conclusion: Together with all these findings, increased NLRP3 expression correlates with favorable prognosis and increased proportion of immune cells in LUAD and SKCM. These conclusions indicate that NLRP3 can serve as a potential biomarker for evaluating prognosis and immune infiltration level.

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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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Expression of LOX Suggests Poor Prognosis in Gastric Cancer

Frontiers in Medicine ◽

10.3389/fmed.2021.718986 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jinfeng Zhu ◽

Chen Luo ◽

Jiefeng Zhao ◽

Xiaojian Zhu ◽

Kang Lin ◽

...

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Logistic Regression ◽

Regression Analysis ◽

Poor Prognosis ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

High Expression ◽

Expression Level ◽

Cox Regression Analysis

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p < 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.

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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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Role of Disease Modifying Treatment in the Risk of Alloimmunization in Transfused Patients with Myelodysplastic Syndromes: A Population-Based Study

Blood ◽

10.1182/blood-2019-123357 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 4253-4253

Author(s):

Hanne Rozema ◽

Robby Kibbelaar ◽

Nic Veeger ◽

Mels Hoogendoorn ◽

Eric van Roon

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Cox Regression ◽

Population Based ◽

Incidence Rates ◽

Blood Products ◽

Cox Regression Analysis ◽

In The Beginning ◽

Observation Period

The majority of patients with myelodysplastic syndromes (MDS) require regular red blood cell (RBC) transfusions. Alloimmunization (AI) against blood products is an adverse event, causing time-consuming RBC compatibility testing. The reported incidence of AI in MDS patients varies greatly. Even though different studies on AI in MDS patients have been performed, there are still knowledge gaps. Current literature has not yet fully identified the risk factors and dynamics of AI in individual patients, nor has the influence of disease modifying treatment (DMT) been explored. Therefore, we performed this study to evaluate the effect of DMT on AI. An observational, population-based study, using the HemoBase registry, was performed including all newly diagnosed MDS patients between 2005 and 2017 in Friesland, a province of the Netherlands. All available information about treatment and transfusions, including transfusion dates, types, and treatment regimens, was collected from the electronic health records and laboratory systems. Follow-up occurred through March 2019. For our patient cohort, blood products were matched for AB0 and RhD, and transfused per the 'type and screen' policy (i.e. electronic matching of blood group phenotype between patient and donor). After a positive antibody screening, antibody identification and Rh/K phenotyping was performed and subsequent blood products were (cross)matched accordingly. The observation period was counted from first transfusion until last transfusion or first AI event. Univariate analyses and cumulative frequency distributions were performed to study possible risk factors and dynamics of AI. DMT was defined as hypomethylating agents, lenalidomide, chemotherapy and monoclonal antibodies. The effect of DMT as a temporary risk period on the risk of AI was estimated with incidence rates, relative risks (RR) and hazard ratios (HR) using a cox regression analysis. Follow-up was limited to 24 months for the cox regression analysis to avoid possible bias by survival differences. Statistical analyses were performed using IBM SPSS 24 and SAS 9.4. Out of 292 MDS patients, 236 patients received transfusions and were included in this study, covering 463 years of follow-up. AI occurred in 24 patients (10%). AI occurred mostly in the beginning of the observation period: Eighteen patients (75%) were alloimmunized after receiving 20 units of RBCs, whereas 22 patients (92%) showed AI after 45 units of RBCs (Figure 1). We found no significant risk factors for AI in MDS patients at baseline. DMT was given to 67 patients (28%) during the observation period. Patients on DMT received more RBC transfusions than patients that did not receive DMT (median of 33 (range: 3-154) and 11 (range: 0-322) RBC units respectively, p<0,001). Four AI events (6%) occurred in patients on DMT and 20 AI events (12%) occurred in patients not on DMT. Cox regression analysis of the first 24 months of follow-up showed an HR of 0.30 (95% CI: 0.07-1.31; p=0.11). The incidence rates per 100 person-years were 3.19 and 5.92 respectively. The corresponding RR was 0.54 (95% CI: 0.16-1.48; p=0.26). Based on our results, we conclude that the incidence of AI in an unselected, real world MDS population receiving RBC transfusions is 10% and predominantly occurred in the beginning of follow-up. Risk factors for AI at baseline could not be identified. Our data showed that patients on DMT received significantly more RBC transfusions but were less susceptible to AI. Therefore, extensive matching of blood products may not be necessary for patients on DMT. Larger studies are needed to confirm the protective effect of DMT on AI. Disclosures Rozema: Celgene: Other: Financial support for visiting MDS Foundation conference.

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Incidence, Survival, and Associated Factors Estimation in Osteosarcoma Patients with Lung Metastasis: A Single-center Experience of 11 Years in Tianjin, China

10.21203/rs.3.rs-1071152/v1 ◽

2021 ◽

Author(s):

Chao Zhang ◽

Haixiao Wu ◽

Guijun Xu ◽

Wenjuan Ma ◽

Lisha Qi ◽

...

Keyword(s):

Risk Factors ◽

Overall Survival ◽

Regression Analysis ◽

Prognostic Factors ◽

Lung Metastasis ◽

Associated Factors ◽

Cox Regression ◽

Cancer Center ◽

Single Center ◽

Cox Regression Analysis

Abstract Background: Osteosarcoma is the most common primary malignant bone tumor. The current study was conducted to describe the general condition of patients with primary osteosarcoma in a single cancer center in Tianjin, China and to investigate the associated factors in osteosarcoma patients with lung metastasis. Methods: From February 2009 to October 2020, patients from Tianjin Medical University Cancer Institute and Hospital, China were retrospectively analyzed. The Kaplan–Meier method was used to evaluate the overall survival of osteosarcoma patients. Prognostic factors of patients with osteosarcoma were identified by the Cox proportional hazard regression analysis. Risk factor of lung metastasis in osteosarcoma were investigated by the logistic regression model. Results: A total of 203 patients were involved and 150 patients were successfully followed up for survival status. The 5-year survival rate of osteo-sarcoma patients was 70.0%. Surgery, bone and lung metastasis were the significant prognostic factors in multivariable Cox regression analysis. Twenty-one (10.3%) patients showed lung metastasis at the diagnosis of osteosarcoma and 67 (33%) lung metastases during the later course. T3 stage (OR=11.415, 95%CI 1.362-95.677, P=0.025) and synchronous bone metastasis (OR=6.437, 95%CI 1.69-24.51, P=0.006) were risk factors of synchronous lung metastasis occurrence. Good necrosis (≥90%, OR=0.097, 95%CI 0.028-0.332, P=0.000) and elevated Ki-67 (≥50%, OR=4.529, 95%CI 1.241-16.524, P=0.022) were proved to be significantly associated with metachronous lung metastasis occurrence. Conclusion: The overall survival, prognostic factors and risk factors for lung metastasis in this single center provided insight about osteosarcoma management.

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