A Population-Based Study: How to Identify High-Risk T1–2 Esophageal Cancer Patients?

BackgroundDue to individualized conditions of lymph node metastasis (LNM) and distant metastasis (DM), the following therapeutic strategy and diagnosis of T1–2 esophageal cancer (ESCA) patients are varied. A prediction model for identifying risk factors for LNM, DM, and overall survival (OS) of high-risk T1–2 ESCA patients is of great significance to clinical practice.MethodsA total of 1,747 T1–2 ESCA patients screened from the surveillance, epidemiology, and end results (SEER) database were retrospectively analyzed for their clinical data. Univariate and multivariate logistic regression models were established to screen out risk factors for LNM and DM of T1-2 ESCA patients, while those of OS were screened out using the Cox regression analysis. The identified risk factors for LNM, DM, and OS were then subjected to the establishment of three nomograms, respectively. The accuracy of the nomograms was evaluated by depicting the calibration curve, and the predictive value and clinical utility were evaluated by depicting the clinical impact curve (CIC) and decision curve analysis (DCA), respectively.ResultsThe age, race, tumor grade, tumor size, and T-stage were significant factors for predicting LNM of T1–2 ESCA patients (p < 0.05). The age, T-stage, tumor grade, and tumor size were significant factors for predicting DM of T1–2 ESCA patients (p < 0.05). The age, race, sex, histology, primary tumor site, tumor size, N-stage, M-stage, and surgery were significant factors for predicting OS of T1–2 ESCA patients (p < 0.05). The C-indexes of the three nomograms constructed by these factors were 0.737, 0.764, and 0.740, respectively, suggesting that they were clinically effective.ConclusionsThe newly constructed nomograms can objectively and accurately predict the LNM, DM, and OS of T1–2 ESCA patients, which contribute to the individualized decision making before clinical management.

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Survival predictors of metastatic angiosarcomas: a surveillance, epidemiology, and end results program population-based retrospective study

BMC Cancer ◽

10.1186/s12885-020-07300-7 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Shihong Ren ◽

Yucheng Wang ◽

Zhan Wang ◽

Jinxiang Shao ◽

Zhaoming Ye

Keyword(s):

Tumor Size ◽

Cox Regression ◽

Radiation Treatment ◽

Tumor Grade ◽

Population Based ◽

Cancer Specific Survival ◽

Cox Regression Analysis ◽

Metastatic Sites ◽

Survival Predictors ◽

End Results

Abstract Background Angiosarcomas (AS) have poor prognosis and often metastasize to distant sites. The potential predictors of metastatic angiosarcomas (MAS) have not been extensively investigated. The main objective of this study was to identify survival predictors of MAS. Methods Surveillance, Epidemiology, and End Results (SEER) datasets were used to identify patients with MAS from 2010 to 2016. Risk predictors were determined with the aid of Kaplan-Meier and Cox regression model analyses. Results A total of 284 MAS patients met the study entry criteria. Among these, 121 patients (42.6%) were diagnosed with metastasis in bone, 26 in brain (9.2%), 86 in liver (30.3%) and 171 in lung (60.2%). Overall, 96 patients (33.8%) had two or more metastatic sites. The 1- and 3-year overall survival (OS) rates were 20.8 and 3.8% while 1- and 3-year cancer-specific survival (CSS) rates were 22.0 and 5.2%, respectively. Cox regression analysis revealed chemotherapy, radiation treatment (RT) and tumor size ≤10 cm as independent favorable predictors of OS. In terms of CSS, tumor grade IV, tumor size > 10 cm and absence of chemotherapy were independent adverse predictors. Surgery did not prolong survival outcomes (both OS and CSS) in the current cohort. Conclusion MAS is associated with extremely poor survival. Chemotherapy, RT, and tumor size are independent predictors of OS. Chemotherapy and tumor size are independent prognostic factors of CSS. Chemotherapy is therefore recommended as the preferred treatment option for MAS patients.

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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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Prognostic factors affecting survival and recurrence in patients with early cervical squamous cell cancer following radical hysterectomy

Journal of International Medical Research ◽

10.1177/0300060519889741 ◽

2019 ◽

Vol 48 (4) ◽

pp. 030006051988974

Author(s):

Dan Li ◽

Xiaoxian Xu ◽

Dingding Yan ◽

Shuhui Yuan ◽

Juan Ni ◽

...

Keyword(s):

Risk Factors ◽

Lymph Node ◽

Squamous Cell ◽

Radical Hysterectomy ◽

Tumor Size ◽

Cox Regression ◽

Squamous Cell Cancer ◽

Postoperative Radiotherapy ◽

Cell Cancer ◽

Cox Regression Analysis

Objective This study aimed to investigate the clinical and histological features affecting the survival of patients with early cervical squamous cell cancer treated with radical hysterectomy. Methods We retrospectively analyzed clinical and histological data for patients with stage IB-IIA cervical cancer treated by radical hysterectomy at Zhejiang Cancer Hospital from August 2008 to January 2013. Results A total of 1435 patients were included in the study. Cox regression analysis identified tumor size >4 cm, lymphovascular space involvement (LVSI), lymph node ratio (LNR), and squamous cell carcinoma antigen (SCC-Ag) >2.65 ng/mL as independent prognostic risk factors. Among 1096 patients without high pathological risk factors, the 5-year local recurrence rates for SCC-Ag ≤2.65 and >2.65 ng/mL were 6.6% and 25.7%, respectively. Among 332 patients with lymph node positivity, the overall survival rates for LNR ≤0.19 and >0.19 were 87.8% and 55.6%, respectively. Conclusions LVSI, tumor size >4 cm, LNR >0.19, and SCC-Ag >2.65 ng/mL may predict a poor prognosis in patients with early cervical squamous cell cancer treated with radical hysterectomy. SCC-Ag >2.65 ng/mL may be a useful prognostic factor guiding the use of postoperative radiotherapy in patients without pathologic risk factors.

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The construction and validation of the model for predicting the incidence and prognosis of brain metastasis in lung cancer patients

10.21203/rs.2.22779/v1 ◽

2020 ◽

Author(s):

Chunjian Zuo ◽

Peng Sun ◽

Guanchu Liu ◽

Pengyu Che ◽

Gang Li ◽

...

Keyword(s):

Risk Factors ◽

Lung Cancer ◽

Brain Metastasis ◽

Calibration Curve ◽

Cox Regression ◽

High Morbidity ◽

Large Sample Size ◽

Operating Characteristics ◽

Primary Tumor Site ◽

Cox Regression Analysis

Abstract Background: Brain metastasis (BM) causes high morbidity and mortality rate in lung cancer (LC). The present study aims to develop models for predicting the development and prognosis of brain metastasis using a large sample size lung cancer cohort. Methods: A total of 266,522 lung cancer cases that were diagnosed between 2010 and 2016 were selected from the Surveillance, Epidemiology, and End Results Program (SEER) cohort. The risk factors for developing BM and prognosis were calculated by uni and multivariable logistic and Cox regression analysis, respectively and nomograms were constructed basing on the risk factors. The performance of the nomogram was evaluated by receiver operating characteristics curve (ROC) or C-index and calibration curve, respectively. Results: The prevalence of BM was 16.25%, the associated factors for developing BM including advanced age, Asian or Pacific Islander race, uninsured status, primary tumor site, higher T stage, N stage, poorly differentiated grade, the presence of lung, liver and bone metastases and adenocarcinoma histology. The median overall survival (OS) was 4 months; the associated prognosis factors were familiar with risk factors plus female gender, unmarried status, and surgery. The calibration curve showed good agreement between predicted and actual probability and the AUC/C-index were 73.1% (95% CI: 72.6-73.6%) and 0.88 (95 % CI 0.87-0.89) for risk and prognosis predictive models, respectively.

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А New Combination of Prognostic Markers in Follicular Lymphoma That Influences the Choice of Therapy

Blood ◽

10.1182/blood-2021-145104 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 4520-4520

Author(s):

Ekaterina S. Nesterova ◽

Nataliya A. Severina ◽

Bella V. Biderman ◽

Andrey B. Sudarikov ◽

Tatiana N. Obukhova ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Follicular Lymphoma ◽

Tumor Size ◽

Cox Regression ◽

Proliferation Index ◽

Ki 67 ◽

Cox Regression Analysis ◽

Risk Of Death ◽

Probability Of Death

Abstract Background: Follicular lymphoma (FL) is characterized by clinical and morphological heterogeneity. It is based on the pathogenetic mechanisms of the development of tumor cells. The identification and assessment of risk factors associated with the course of the disease and treatment outcome in FL is an important task, as it allows to evaluate and predict the effectiveness of therapy. Objective: Identify and estimate risk factors for overall survival (OS) and progression free survival (PFS) in FL. Patients and Methods: The prospective exploratory study conducted at National Research Center for Hematology (Moscow) from 01/2017 to 04/2021 included patients (pts)(in total, 80) with FL. Morpho-immunohistochemical, cytogenetic and molecular studies were performed on biopsies of lymph nodes taken before the start of therapy. The mutational status of exon 16 and intron polymorphism rs_2072407 of the EZH2 gene were investigated by Sanger sequencing. 18q21/BCL-2 rearrangements were determined by conventional cytogenetic analysis and/or FISH study. The results obtained in a blind study were compared with the effect of the therapy. Results: Of the 80 pts 34 were male: Me (median) age 50 years (range 30-72) and 46 were female: Me 56 (range 21-81). The median follow-up (FU) time was 53 months. As a result of the study in the multivariate Cox regression model (likelihood-ratio test, p=0.01) of significant factors, selected in the previously univariate analysis, the following statistically significant (Wald test) risk factors for OS and PFS (the events: progression, relapse, or death) were obtained: • BCL-2 gene rearrangements (no vs yes) • EZH2 gene genotypes (AA/AG vs GG) • proliferation index Ki-67 (>35%) • morphological grade (3А vs 1/2) • tumor size (>6 cm /bulky/) (Tab. 1, Fig. 1) The BCL-2 rearrangements were found in 45 from 80 pts (56%; 95 % CI 45-66). The probability of BCL-2 rearrangements is estimated to be about 0.5 (50%). According to the results of Cox-regression analysis (by OS) in the absence of BCL-2 rearrangements, the risk of death in FL was generally significantly (p = 0.01) higher than in the group with its presence: HR = 4.3 (95 % CI 1.5-13.0) (Fig. 2) Mutations in the 16th exon of the EZH2 gene (mutEZH2) were found in 10/80 (13%) pts. Analysis of EZH2 gene mutations with BCL-2 rearrangements revealed that in the mutEZH2 group with the presence of BCL-2 rearrangements, the number of deaths associated with progression is significantly less than in the control initial groups (mutEZH2 with BCL-2 rearrangements - 0/6, mutEZH2 without BCL-2 rearrangements - 2/4, wEZH2 with BCL-2 rearrangements - 3/39 (8%), wEZH2 without BCL-2 rearrangements - 11/31 (35%)) . The prognostic significance of EZH2 genotypes in lymphomas was studied for the first time in this study. The frequencies of rs_2072407 genotypes were: AA - 24% (19), AG - 42% (34), and GG - 34% (27). AA and AG genotypes of the EZH2 gene in pts with FL were associated with an increased risk of death (compared to the GG genotype) : HR = 2.9 (95% CI: 1.2-10.6), p = 0.01 (Fig. 3). The GG variant in most cases was associated with wEZH2 (26/27 (96%)) with BCL-2 rearrangements (16/26 (62%)) and a favorable prognosis (26/27 (96%)) (p = 0.01). Index of proliferative activity Ki-67> 35% (n = 40) and Ki-67 ≤ 35% (n = 40) were equally common in the study group. With a Ki-67> 35%, the probability of death is 2.9 (95% CI 1.1-9.7) times higher. The frequency distribution of morphological grade was as follows: grade 3A - 53% (n = 43) and grade 1-2 - 47% (n = 37). At grade 3A, the probability of death is 2.5 (95% CI 1.1-7.8) times higher. The number of pts with tumor size >6 cm (bulky) and ≤ 6 cm in the sample is approximately the same (41 and 39, respectively), the presence of bulky increased the mortality risk by 2.1 (95% CI 1.0-6.5) times. A short time from the manifestation of the disease to appeal to medical care is a predictor of poor prognosis, but this result we received earlier on a large sample of pts was not significant on a smaller sample. Conclusions: As a result of the multivariable Cox regression analysis, we identified and confirmed the previously obtained factors (bulky, grade 3A, Ki-67 > 35%, short medical history), and discovered new biogenetic factors (BCL-2 rearrangements and the GG rs2072407 genotype of the EZH2 gene). The model based on these independent risk factors improves the accuracy of predicting adverse events and allows to use more personalized treatment options for patients with FL. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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Independent Risk Factor Analysis for Major Cardiovascular Adverse Events in Patients with Mild Coronary Stenosis

10.21203/rs.2.14615/v1 ◽

2019 ◽

Author(s):

Wei Luo ◽

Ru Zhao ◽

YanQiu Song ◽

Hui Zhao ◽

WeiJun Ma ◽

...

Keyword(s):

Risk Factors ◽

High Risk ◽

Coronary Stenosis ◽

Cox Regression ◽

Risk Group ◽

Adverse Cardiovascular Event ◽

Cox Regression Analysis ◽

Significant Difference ◽

Independent Risk Factors ◽

Hs Crp

Abstract Background: Independent risk factors for major adverse cardiovascular event (MACE) in patients with mild coronary stenosis are uncertain. This study aims to predict high-risk plaques detected by coronary computed tomographic angiography (CCTA) associated with indicative biomarkers.Methods: Totally 381 patients with mild coronary stenosis were included and MACE incidences were recorded through a 24-month follow-up. Totally 91 high-risk plaques are detected by CCTA, dividing into three plaque groups: high-risk group (HR), intermediate-risk group (IR) and low-risk group (LR). Specific blood biomarker measurements of hs-CRP, MMP-9, and MPO were taken simultaneously.Results: The mean age, levels of hs-CRP and MPO in HR and IR group were significantly higher than LR group. A considerably higher level of MMP-9 showed in HR group compared to LR group. The incidence rates of MACE were remarkably higher in HR group than LR group and IR group. Kaplan—Meier survival analysis demonstrated that the cumulative event—free survival rate of HR was significantly higher than that in LR and IR group and there were no significant difference between LR and IR group. The univariate COX regression analysis indicated that the age of patients, hs-CRP, MPO, and high-risk plaque scores≥2 were independent risk factors for MACE. Conclusion: Age, levels of hs-CRP and MPO, and high-risk plaque features informed by CCTA independently predicted MACE in patients with mild coronary stenosis. These results may improve the risk stratification in patients with mild coronary stenosis and suggest strategies for the individualized prevention programs.

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Clinical Characteristics and Survival Outcomes in Neuroblastoma With Bone Metastasis Based on SEER Database Analysis

Frontiers in Oncology ◽

10.3389/fonc.2021.677023 ◽

2021 ◽

Vol 11 ◽

Author(s):

Bin He ◽

Jianshui Mao ◽

Leyi Huang

Keyword(s):

Risk Factors ◽

Survival Analysis ◽

Bone Metastasis ◽

Clinical Features ◽

Lung Metastasis ◽

Tumor Size ◽

Treatment Modalities ◽

Seer Database ◽

Primary Tumor Site ◽

Cox Regression Analysis

PurposeClinical features and survival analysis of neuroblastoma (NB) are well explored. However, clinical research of NB patients with bone metastasis is rarely reported. Thus, the current study was performed to analyze the clinical features, survival outcome, and risk factors in those patients.Materials and MethodsWe reviewed the Surveillance, Epidemiology, and End Results (SEER) database to select cases diagnosed with NB with bone metastasis from 2010 to 2016. Overall survival (OS) and cancer-specific survival (CSS) were analyzed through univariate Cox regression analysis. Subsequently, we performed multivariate analysis to determine independent predictors of survival. The Kaplan–Meier method was applied to intuitively show differences in prognostic value between independent risk factors.ResultsWe finally identified 393 NB patients with bone metastasis who were selected for survival analysis. Nearly half of the patients (47.3%) were aged >3 years. The adrenal gland was the primary tumor site, accounting for approximately two thirds of cases (66.2%). The 5-year OS and CSS rates of all patients were 62.1% and 64.1%, respectively. The univariate analysis indicated that age, lung metastasis, and tumor size were significantly associated with OS and CSS. Based on the multivariable analysis, age at 2 and 3 years, lung metastasis, and tumor size >10 cm remained significant negative predictors of OS and CSS.ConclusionFor NB patients with bone metastasis, three independent prognostic risk factors (age, lung metastasis, and tumor size) are helpful to clinicians for predicting prognosis and guiding treatment. Reasonable treatment modalities for these patients should be further investigated to prolong survival.

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Duodenal neuroendocrine tumors: Somewhere between the pancreas and small bowel?

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.4_suppl.377 ◽

2019 ◽

Vol 37 (4_suppl) ◽

pp. 377-377 ◽

Cited By ~ 1

Author(s):

Adriana Carolina Gamboa ◽

Yuan Liu ◽

Mohammad Yahya Zaidi ◽

Rachel M Lee ◽

Maria C. Russell ◽

...

Keyword(s):

Small Bowel ◽

Propensity Score ◽

Neuroendocrine Tumors ◽

Tumor Size ◽

Cox Regression ◽

Tumor Grade ◽

Excisional Biopsy ◽

Cox Regression Analysis ◽

Regional Lymphadenectomy ◽

Clinicopathologic Factors

377 Background: While small sub-2 cm pancreatic neuroendocrine tumors (NETs) are often observed given their indolent behavior, small bowel NETs are routinely resected with a regional lymphadenectomy regardless of size given their malignant potential. Considering this variability, our aim was to define the natural history of duodenal (D-NETs) and determine the role of resection. Secondary aim was to define clinicopathologic factors associated with overall survival (OS) in pts who undergo resection. Methods: All pts in the National Cancer Database (2004-14) diagnosed with non-metastatic, non-functional D-NETs were included. Local resection (LR) was defined as local excision, polypectomy, or excisional biopsy. Anatomic resection (AR) was defined as removal with radical surgery. Tumor size was divided into three categories (< 1 cm, 1-2 cm, ≥ 2 cm). Propensity score weighting analysis was used to create balanced cohorts between resection and no-resection pts; this was maintained in all three size categories. Primary endpoint was OS. Results: Among 5,502 pts, median age was 65 yrs; 52% were male. Median f/u was 51 mos. Median tumor size was 0.8 cm. Resection was performed in 72% (n = 3954) of which 61% were LR and 39% were AR. At least one lymph node (LN) was retrieved in 25% of pts, of which 44% had LN metastasis. 74% had negative margins. Resection and no-resection cohorts were propensity score weighted for age, gender, race, Charlson-Deyo score, and tumor grade, all of which were independently associated with OS on MV Cox regression analysis, thus creating balanced cohorts. Resection was associated with improved median OS compared to no-resection (MNR vs 94 mos, p < 0.01); this persisted for all three size categories (< 1 cm: MNR vs 194 mos; 1-2 cm: MNR vs 56 mos; > 2 cm: MNR vs 90 mos; all p < 0.01). Subset analysis of each size cohort who underwent resection showed that neither type of resection, LN retrieval, LN positivity, or margin status was associated with OS (all p > 0.05). Conclusions: All pts with non-metastatic non-functional D-NETs should be considered for resection regardless of tumor size. Given their lack of prognostic value, the type of resection and extent of LN retrieval should be tailored to the patient’s clinical picture and safety profile.

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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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Prognostic Factors and Diseases-Specific Survival Outcome in Patients with Glioblastoma: A Population-Based Study

10.21203/rs.3.rs-111364/v1 ◽

2020 ◽

Author(s):

Lihua Wu ◽

Jianbo Song ◽

Junping Zhang ◽

Wenhui Yang ◽

Mengxian Zhang ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Prognostic Factors ◽

Tumor Size ◽

Cox Regression ◽

Cubic Spline ◽

Age At Diagnosis ◽

Lasso Regression ◽

Cox Regression Analysis ◽

Risk Effect

Abstract ObjectiveThis study aimed to determine the prognostic factors for disease-specific survival (DSS) of glioblastoma (GBM) and establish a corresponding effective nomogram for clinical prediction.Methods This study was based on Surveillance, Epidemiology, and End Results database between 2004 and 2015. Kaplan-Meier survival analysis was used to evaluate the effect of various prognostic factors on DSS. Lasso regression was used to determine the independent prognostic factors of DSS and multivariate cox regression analysis was performed correspondingly. Additional restricted cubic spline cox regression was used to analyze the trend of the risk effect (hazard ratio) of continuous variables on DSS. Based on the multivariate cox regression model, a nomogram was established to predict DSS. ResultsThe average age at diagnosis of all enrolled patients was 59.8±12.2 years, of which 40.5% were women and 59.5% were men. Lasso regression analysis showed that age at diagnosis, sex, marital status, race, tumor size, primary site, laterality, surgery, radiotherapy and chemotherapy, radiotherapy sequence with surgery, and year of diagnosis were independent prognostic factors for DSS. Multivariate cox regression analysis showed that elderly, males, unmarried status, larger tumors were all risk factors for DSS. Restricted cubic spline cox regression showed that the risk of death from GBM was significantly increased for the elderly, especially older than 75 years. When the tumor was smaller than 75mm, an increasing risk linearly was associated with DSS, but the risk effect remained constant after 75mm. Constructing the nomogram to predict the DSS probability of 1-, 3- and 5-year respectively, and its good predictive performance was proved by the calibration curve.ConclusionThe advanced age was one of the significant risk factors for GBM. How the change of tumor size affected DSS needed further study and discussion. The established nomogram was robust in predicting 1-, 3-, and 5- year DSS.

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