Rebleeding of Ruptured Intracranial Aneurysm After Admission: A Multidimensional Nomogram Model to Risk Assessment

ObjectiveRebleeding is recognized as the main cause of mortality after intracranial aneurysm rupture. Though timely intervention can prevent poor prognosis, there is no agreement on the surgical priority and choosing medical treatment for a short period after rupture. The aim of this study was to investigate the risk factors related to the rebleeding after admission and establish predicting models for better clinical decision-making.MethodsThe patients with ruptured intracranial aneurysms (RIAs) between January 2018 and September 2020 were reviewed. All patients fell to the primary and the validation cohort by January 2020. The hemodynamic parameters were determined through the computational fluid dynamics simulation. Cox regression analysis was conducted to identify the risk factors of rebleeding. Based on the independent risk factors, nomogram models were built, and their predicting accuracy was assessed by using the area under the curves (AUCs).ResultA total of 577 patients with RIAs were enrolled in this present study, 86 patients of them were identified as undergoing rebleeding after admission. Thirteen parameters were identified as significantly different between stable and rebleeding aneurysms in the primary cohort. Cox regression analysis demonstrated that six parameters, including hypertension [hazard ratio (HR), 2.54; P = 0.044], bifurcation site (HR, 1.95; P = 0.013), irregular shape (HR, 4.22; P = 0.002), aspect ratio (HR, 12.91; P < 0.001), normalized wall shear stress average (HR, 0.16; P = 0.002), and oscillatory stress index (HR, 1.14; P < 0.001) were independent risk factors related to the rebleeding after admission. Two nomograms were established, the nomogram including clinical, morphological, and hemodynamic features (CMH nomogram) had the highest predicting accuracy (AUC, 0.92), followed by the nomogram including clinical and morphological features (CM nomogram; AUC, 0.83), ELAPSS score (AUC, 0.61), and PHASES score (AUC, 0.54). The calibration curve for the probability of rebleeding showed good agreement between prediction by nomograms and actual observation. In the validation cohort, the discrimination of the CMH nomogram was superior to the other models (AUC, 0.93 vs. 0.86, 0.71 and 0.48).ConclusionWe presented two nomogram models, named CMH nomogram and CM nomogram, which could assist in identifying the RIAs with high risk of rebleeding.

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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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Cox Regression Analysis of 1739 Emergency Trauma Patients

10.21203/rs.3.rs-29650/v1 ◽

2020 ◽

Author(s):

Jun Shen ◽

Feng Xu ◽

Du Chen

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Oxygen Saturation ◽

Cox Regression ◽

Trauma Patients ◽

Term Survival ◽

Cox Regression Analysis ◽

Revised Trauma Score ◽

Independent Risk Factors ◽

Trauma Score

Abstract BACKGROUND: Trauma is a damage caused by physical harm from external source. It has been one of the major causes of mortality. The purpose of this study was to explore the risk factors related to mortality among emergency trauma patients. METHODS: This was a retrospective study in trauma center of the First Affiliated Hospital of Soochow University. The data were obtained from trauma database with patients registered from November 1, 2016 to November 30, 2019.Shapiro–Wilk test, Mann-Whitney test and Likelihood-ratio Chi squared test were used to assess the survival pattern. Cox regressions were performed to calculate the hazard ratios (HRs) of variables for death. RESULTS: The total 1739 emergency trauma patients, 44 (2.53%) died during the study period and 1695 (97.47%) were survival. Through univariable and multivariable Cox regression analysis, three independent risk factors for emergency death were screened out: pulse (Crude HR: 0.97, 95% Confidence Interval [CI]: 0.96-0.98; Adjuste HR: 1.04, 95% CI: 1.02-1.06), pulse oxygen saturation (Crude HR: 0.96, 95% CI: 0.95-0.97; Adjuste HR: 0.94, 95% CI: 0.91-0.97) and Revised Trauma Score (Crude HR: 0.69, 95% CI: 0.65-0.74; Adjuste HR: 0.79, 95% CI: 0.64-0.97).CONCLUSION: The survival outcome of emergency trauma patients was influenced by many factors. Pulse, pulse oxygen saturation (SpO2 ) and Revised Trauma Score (RTS) were the independent risk factors for mortality. Accurate analysis and judgment of the risk factors can improve cure efficiency and long-term survival rate.

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Coagulopathy on the first postoperative day predicting the long-term survival of traumatic brain injury patients

10.21203/rs.2.23641/v1 ◽

2020 ◽

Author(s):

Wenxing Cui ◽

Shunnan Ge ◽

Yingwu Shi ◽

Xun Wu ◽

Jianing Luo ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Cox Regression ◽

Term Survival ◽

Long Term Survival ◽

Cox Regression Analysis ◽

Independent Risk Factors ◽

The Relationship ◽

Underlying Risk

Abstract Objective: The purpose of this study was to identify the relationship between coagulopathy during the perioperative period (before the operation and on the first day after the operation) and the long-term survival of TBI patients undergoing surgery, as well as to explore the predisposing risk factors that may cause perioperative coagulopathy.Methods: This retrospective study included 447 TBI patients who underwent surgery from January 1, 2015 to April 25, 2019. Clinical parameters, including patient demographic characteristics, biochemical tests, perioperative coagulation function tests (before the operation and on the first day after the operation) and intraoperative factors were collected. Log-rank univariate analysis and Cox regression models were conducted to assess the relationship between perioperative coagulopathy and the long-term survival of TBI patients. Furthermore, univariate and multivariate analyses were performed to identify the underlying risk factors for perioperative coagulopathy.Results: Multivariate Cox regression analysis identified age, AIS(head) = 5, GCS ≤ 8, systolic pressure at admission < 90 mmHg and postoperative coagulopathy (all P < 0.05) as independent risk factors for survival following TBI; we were the first to identify postoperative coagulopathy as an independent risk factor. According to multivariate logistic regression analysis, for the first time, abnormal ALT and RBC at admission, preoperative coagulopathy, infusion of colloidal solution > 1100 mL and intraoperative bleeding > 950 mL (all P < 0.005) were identified as independent risk factors for postoperative coagulation following surgery after TBI.Conclusions: Those who suffered from postoperative coagulopathy due to TBI had a higher hazard for poor prognosis than those who did not. Closer attention should be paid to postoperative coagulopathy and more emphasis should be placed on managing the underlying risk factors.

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Characteristic and Early Discontinuation of Obsessive-Compulsive Disorder Trials Registered on ClinicalTrials.gov

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.650057 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shanxia Luo ◽

Qiong Guo ◽

Liu Yang ◽

Yifan Cheng ◽

Youlin Long ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Obsessive Compulsive Disorder ◽

Cox Regression ◽

Drug Trials ◽

Obsessive Compulsive ◽

Early Discontinuation ◽

Cox Regression Analysis ◽

Compulsive Disorder ◽

Independent Risk Factors

Objective: This study aimed to analyze the characteristics and reasons of early discontinuation of obsessive-compulsive disorder (OCD) trials registered on ClinicalTrials.gov.Methods: OCD trials and relevant publications were searched on ClinicalTrials.gov and PubMed, respectively. The characteristics and details regarding the timely publication of trials were recorded. Cox regression analysis was used to explore factors associated with the early discontinuation of OCD trials.Results: The analysis included 298 OCD therapy trials. Most investigations recruited <100 patients and were more likely to involve adults. Of all OCD studies identified, 67.8% were randomized and 61.4% were blind (single- or double-blind). Universities and hospitals were recorded as the two primary locations in the majority of trials. A total of 155 trials (52%) were completed; however, only 29% of those were published. Of the published trials, >70% were published at least 1 year after completion. Behavioral therapy trials were the most common type of major treatment-aimed OCD trials (39%), followed by drug trials (35.1%) and device/procedure trials (24.7%). The univariate Cox regression analysis indicated that drug trials [hazard ratio (HR) = 2.56, 95% confidence interval (CI): 1.21–5.43], absence of collaborators (HR = 3.87, 95% CI: 1.62–9.26), and sponsorship by industry (HR = 3.97, 95% CI: 1.49–10.53) were risk factors for early discontinuation of OCD trials. Further multivariate Cox regression showed that drug trials (HR = 3.93, 95% CI: 1.71–9.08) and absence of collaborators (HR = 5.17, 95% CI: 1.97–13.54) were independent risk factors for early trial discontinuation of OCD trials. The sensitivity analysis confirmed these results. Non-drug trials (OR = 3.32, 95% CI: 1.21–9.11), absence of collaborators (OR = 3.25, 95% CI: 1.10–9.60), and non-blinded trials (OR = 5.23, 95% CI: 1.05–26.2) were independent risk factors for unreported results in registry.Conclusion: The diagnosis and prevention of OCD are rarely investigated in trials. Underreporting and delayed reporting remain major problems. The type of intervention and participation of collaborators are associated with early discontinuation of OCD trials.

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Effect of cumulative dexamethasone dose during concomitant chemoradiation on lymphopenia in patients with newly diagnosed glioblastoma.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e14533 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e14533-e14533

Author(s):

Stephen Ahn ◽

Jae-Sung Park ◽

Jin Ho Song ◽

Sin-Soo Jeun ◽

Yong-Kil Hong

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Cox Regression ◽

Performance Status ◽

Multivariate Logistic Regression Analysis ◽

Newly Diagnosed ◽

Cox Regression Analysis ◽

Female Sex ◽

Concomitant Chemoradiation ◽

Independent Risk Factors

e14533 Background: Lymphopenia frequently occurs after concomitant chemoradiation (CCRT) in patients with glioblastoma (GBM) and is associated with worse overall survival (OS). A few studies have tried to identify risk factors for lymphopenia; however, the results were not clear. We aimed to identify potential risk factors for lymphopenia, focusing on the use of dexamethasone to control cerebral edema in patients with GBM. Methods: The electronic medical records of 180 patients with newly diagnosed GBM treated at our institution between 2009 and 2017 were retrospectively examined. Acute lymphopenia was defined as TLC (total lymphocyte count) less than 1,000 cells/mm3 at 4 weeks after completion of CCRT. Multivariate logistic regression analysis was used to identify independent risk factors for lymphopenia, and Cox regression analysis was used to identify independent risk factors for OS. Results: Of the 125 eligible patients, 40 patients (32.0%) developed acute lymphopenia. Female sex and median daily dexamethasone dose > 2mg after initiation of CCRT were independent risk factors for acute lymphopenia on multivariate analysis. Acute lymphopenia, extent of surgical resection, and performance status were associated with OS; however, dexamethasone use itself was not an independent risk factor for poor OS. Conclusions: Female sex, median daily dexamethasone dose > 2 mg after initiation of CCRT until four weeks after completion of CCRT may be associated with acute lymphopenia. However, dexamethasone use itself did not affect OS in patients newly diagnosed with GBM. These results should be validated by further prospective studies controlling for other confounding factors.

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Aneurysm Size is the Strongest Risk Factor for Intracranial Aneurysm Growth in the Eastern Finnish Population

Neurosurgery ◽

10.1093/neuros/nyy161 ◽

2018 ◽

Vol 84 (5) ◽

pp. 1098-1103 ◽

Cited By ~ 2

Author(s):

Joel Björkman ◽

Juhana Frösen ◽

Olli Tähtinen ◽

Terhi Huttunen ◽

Jukka Huttunen ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Risk Factor ◽

Intracranial Aneurysm ◽

Cox Regression ◽

Finnish Population ◽

Cox Regression Analysis ◽

Aneurysm Size ◽

Aneurysm Growth

Abstract BACKGROUND Saccular intracranial aneurysm (sIA) growth during follow-up is associated with high risk for subsequent rupture. Finnish patients have been suggested to have higher risk for subarachnoid hemorrhage, but follow-up studies of sIA growth in the Finnish population are scarce. OBJECTIVE To identify the strongest risk factors for sIA growth in Eastern Finnish population by studying 205 patients with 350 unruptured sIAs with angiographic follow-up imaging. METHODS In this population-based cohort study, we included unruptured sIA patients from the Kuopio University Hospital Intracranial Aneurysm Patient and Family database with at least 6 mo of angiographic follow-up after the diagnosis of sIAs. Angiograms were re-evaluated to detect aneurysms with growth of at least 1.0 mm. Cox regression analysis with patient- and aneurysm-related risk factors was used to calculate hazard ratios with 95% confidence intervals for growth. In addition, we tested the diagnostic value of previously introduced PHASES score for the prediction of sIA growth in Eastern Finnish population. RESULTS Of the 350 unruptured aneurysms, 36 (10.3%) showed growth during median follow-up of 1.7 yr and total follow-up of 790 yr. In the multivariate Cox regression analysis, sIA size and location in the middle cerebral artery were significant risk factors for sIA growth. In receiver operator characteristic curves, both PHASES score and sIA size had relatively low areas under the curve. CONCLUSION Our study indicates that aneurysm size is the strongest risk factor for aneurysm growth in Eastern Finnish population. Further studies are required to identify new risk factors for aneurysm growth.

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Risk of Hepatocellular Carcinoma Remains High in Patients with HBV-Related Decompensated Cirrhosis and Long-Term Antiviral Therapy

Canadian Journal of Gastroenterology and Hepatology ◽

10.1155/2020/8871024 ◽

2020 ◽

Vol 2020 ◽

pp. 1-6

Author(s):

Dong-Mei Zhu ◽

Jing Xie ◽

Chun-Yan Ye ◽

Mei-Yun Qian ◽

Yuan Xue

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Antiviral Therapy ◽

Cox Regression ◽

Decompensated Cirrhosis ◽

Cox Regression Analysis ◽

Independent Risk Factors ◽

The Difference

Background. This study aimed to evaluate the risk factors of HCC development in patients with hepatitis B virus (HBV)-related DC and who underwent long-term antiviral therapy. Methods. Data from 308 patients with HBV-related DC and long-term antiviral therapy were collected and retrospectively reviewed. Cox regression analysis was used to analyze independent risk factors of HCC development. Results. Data from 129 patients with definite records were analyzed. The median follow-up time was 5 years (range, 1 to 8 years). At the end of the follow-up, 41 (31.8%) patients developed HCC, and the time from DC diagnosis to HCC incidence who received antiviral therapy was 4.4 years (range, 1–7 years). The incidence of HCC was higher in males (30/78, 38.5%) than in females (11/51, 21.6%) ( P = 0.04). Patients who developed HCC were significantly older than those who did not develop HCC ( P < 0.01). The incidence of HCC in patients receiving nucleoside analogues, nucleotide analogues, and combination therapy was 34.7%, 38.1%, and 33.3%, respectively, and the difference showed no significant differences ( P = 0.95). Multivariate Cox regression analysis demonstrated that male gender and age ≥50 years are independent risk factors of HCC development (OR = 2.987 and 2.408; 95% CI (1.301–6.858) and (1.126–5.149); P = 0.01 and 0.02, respectively). Conclusion. The risk of HCC remains to be high in patients with HBV-related DC, especially in males aged ≥50 years.

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Nomogram for Predicting COVID-19 Disease Progression Based on Single-Center Data: Observational Study and Model Development (Preprint)

10.2196/preprints.19588 ◽

2020 ◽

Author(s):

Tao Fan ◽

Bo Hao ◽

Shuo Yang ◽

Bo Shen ◽

Zhixin Huang ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Clinical Characteristics ◽

Cox Regression ◽

Disease Onset ◽

Lasso Regression ◽

Prediction Ability ◽

Calibration Curves ◽

Independent Risk Factors ◽

Critical Patients

BACKGROUND In late December 2019, a pneumonia caused by SARS-CoV-2 was first reported in Wuhan and spread worldwide rapidly. Currently, no specific medicine is available to treat infection with COVID-19. OBJECTIVE The aims of this study were to summarize the epidemiological and clinical characteristics of 175 patients with SARS-CoV-2 infection who were hospitalized in Renmin Hospital of Wuhan University from January 1 to January 31, 2020, and to establish a tool to identify potential critical patients with COVID-19 and help clinical physicians prevent progression of this disease. METHODS In this retrospective study, clinical characteristics of 175 confirmed COVID-19 cases were collected and analyzed. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select variables. Multivariate analysis was applied to identify independent risk factors in COVID-19 progression. We established a nomogram to evaluate the probability of progression of the condition of a patient with COVID-19 to severe within three weeks of disease onset. The nomogram was verified using calibration curves and receiver operating characteristic curves. RESULTS A total of 18 variables were considered to be risk factors after the univariate regression analysis of the laboratory parameters (P<.05), and LASSO regression analysis screened out 10 risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were age (OR 1.035, 95% CI 1.017-1.054; P<.001), CK level (OR 1.002, 95% CI 1.0003-1.0039; P=.02), CD4 count (OR 0.995, 95% CI 0.992-0.998; P=.002), CD8 % (OR 1.007, 95% CI 1.004-1.012, P<.001), CD8 count (OR 0.881, 95% CI 0.835-0.931; P<.001), and C3 count (OR 6.93, 95% CI 1.945-24.691; P=.003). The areas under the curve of the prediction model for 0.5-week, 1-week, 2-week and 3-week nonsevere probability were 0.721, 0.742, 0.87, and 0.832, respectively. The calibration curves showed that the model had good prediction ability within three weeks of disease onset. CONCLUSIONS This study presents a predictive nomogram of critical patients with COVID-19 based on LASSO and Cox regression analysis. Clinical use of the nomogram may enable timely detection of potential critical patients with COVID-19 and instruct clinicians to administer early intervention to these patients to prevent the disease from worsening.

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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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