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Xiong Y, Qiao W, Mei T, Li K, Jin R, Zhang Y. Recurrence of Hepatocellular Carcinoma in Patients with Low Albumin-Bilirubin Grade in TACE Combined with Ablation: A Random Forest Cox Predictive Model. J Hepatocell Carcinoma 2024; 11:1375-1388. [PMID: 39005969 PMCID: PMC11245575 DOI: 10.2147/jhc.s465962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 06/06/2024] [Indexed: 07/16/2024] Open
Abstract
Purpose The aim of our study was to investigate the relationship between albumin-bilirubin (ALBI) grade and recurrence in patients who underwent TACE sequential ablation. We developed and validated a nomogram to predict low levels of ALBI patients' recurrence. Patients and Methods A total of 880 patients undergoing TACE combined ablation at Beijing Youan Hospital from January 2014 to December 2021 were retrospectively enrolled, including 415 patients with L-ALBI (≤-2.6) and 465 patients with high levels (>-2.6) of ALBI (H-ALBI). L-ALBI patients were randomized in a 7:3 ratio into the training cohort (N=289) and validation cohort (N=126). Multivariate Cox regression followed by random survival forest was carried out to identify independent risk factors for prediction nomogram construction. An examination of nomogram accuracy was performed using the C-index, receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA) curves. According to the nomogram, the patients were divided into low-risk, intermediate-risk, and high-risk groups. Kaplan-Meier (KM) curves were applied to compare the difference in recurrence-free survival (RFS) among the three groups. Results The median RFS in L-ALBI patients was significantly longer than the H-ALBI patients (40.8m vs 20.1m, HR:1.71, 95% CI:1.44-2.04, P<0.0001). The nomogram was composed of five variables, such as age, Barcelona Clinic Liver Cancer (BCLC) stage, globulin, gamma-glutamyl transferase to lymphocyte ratio (GLR), and international normalized ratio (INR). The C-index (0.722 and 0.731) and 1-, 3-, and 5-year AUCs (0.725, 0.803, 0.870, and 0.764, 0.816, 0.798) of the training and validation cohorts proved the good predictive performance of the nomogram. Calibration curves and DCA curves demonstrated good consistency and good clinical utility. There were significant differences in RFS between the low-risk, intermediate-risk, and high-risk groups (P<0.0001). Conclusion L-ALBI Patients who underwent TACE combined ablation had better recurrence-free survival than patients with H-ALBI. The nomogram developed and validated in our study had good predictive ability in recurrence for L-ALBI patients.
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Affiliation(s)
- Yiqi Xiong
- Interventional Therapy Center for Oncology, Beijing You'an Hospital, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Wenying Qiao
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People's Republic of China
- Changping Laboratory, Beijing, 102206, People's Republic of China
| | - Tingting Mei
- Interventional Therapy Center for Oncology, Beijing You'an Hospital, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Kang Li
- Research center for biomedical Resources, Beijing You'an Hospital, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Ronghua Jin
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People's Republic of China
- Changping Laboratory, Beijing, 102206, People's Republic of China
| | - Yonghong Zhang
- Interventional Therapy Center for Oncology, Beijing You'an Hospital, Capital Medical University, Beijing, 100069, People's Republic of China
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Xiong Y, Qiao W, Wang Q, Li K, Jin R, Zhang Y. Construction and validation of a machine learning-based nomogram to predict the prognosis of HBV associated hepatocellular carcinoma patients with high levels of hepatitis B surface antigen in primary local treatment: a multicenter study. Front Immunol 2024; 15:1357496. [PMID: 38601167 PMCID: PMC11004323 DOI: 10.3389/fimmu.2024.1357496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 03/19/2024] [Indexed: 04/12/2024] Open
Abstract
Background Hepatitis B surface antigen (HBsAg) clearance is associated with improved long-term outcomes and reduced risk of complications. The aim of our study was to identify the effects of levels of HBsAg in HCC patients undergoing TACE and sequential ablation. In addition, we created a nomogram to predict the prognosis of HCC patients with high levels of HBsAg (≥1000U/L) after local treatment. Method This study retrospectively evaluated 1008 HBV-HCC patients who underwent TACE combined with ablation at Beijing Youan Hospital and Beijing Ditan Hospital from January 2014 to December 2021, including 334 patients with low HBsAg levels and 674 patients with high HBsAg levels. The high HBsAg group was divided into the training cohort (N=385), internal validation cohort (N=168), and external validation cohort (N=121). The clinical and pathological features of patients were collected, and independent risk factors were identified using Lasso-Cox regression analysis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts. Patients were classified into high-risk and low-risk groups based on the risk scores of the nomogram. Result After PSM, mRFS was 28.4 months (22.1-34.7 months) and 21.9 months (18.5-25.4 months) in the low HBsAg level and high HBsAg level groups (P<0.001). The content of the nomogram includes age, BCLC stage, tumor size, globulin, GGT, and bile acids. The C-index (0.682, 0.666, and 0.740) and 1-, 3-, and 5-year AUCs of the training, internal validation, and external validation cohorts proved good discrimination of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classification of patients with high HBsAg levels into low-risk and high-risk groups according to the risk of recurrence. There was a statistically significant difference in RFS between the two groups in the training, internal validation, and external validation cohorts (P<0.001). Conclusion High levels of HBsAg were associated with tumor progression. The nomogram developed and validated in the study had good predictive ability for patients with high HBsAg levels.
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Affiliation(s)
- Yiqi Xiong
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Wenying Qiao
- Research Center for Biomedical Resources, Beijing You’an Hospital Capital Medical University, Beijing, China
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Qi Wang
- Interventional Radiology Department, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Kang Li
- Research Center for Biomedical Resources, Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Ronghua Jin
- Research Center for Biomedical Resources, Beijing You’an Hospital Capital Medical University, Beijing, China
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Yonghong Zhang
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
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Qiao W, Sheng S, Li J, Jin R, Hu C. Machine Learning-Based Nomogram for Predicting Overall Survival in Elderly Patients with Cirrhotic Hepatocellular Carcinoma Undergoing Ablation Therapy. J Hepatocell Carcinoma 2024; 11:509-523. [PMID: 38468611 PMCID: PMC10926877 DOI: 10.2147/jhc.s450825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 02/27/2024] [Indexed: 03/13/2024] Open
Abstract
Purpose The aim of the study is to identify and evaluate multifaceted factors impacting the survival of elderly cirrhotic HCC patients following ablation therapy, with the goal of constructing a nomogram to predict their 3-, 5-, and 8-year overall survival (OS). Patients and Methods A retrospective analysis was conducted on 736 elderly cirrhotic HCC patients who underwent ablation therapy between 2014 and 2022. LASSO regression, random survival forest (RSF), and multivariate Cox analyses were employed to identify independent prognostic factors for OS, followed by the development and validation of a predictive nomogram. Harrell's concordance index (C-index), calibration plot and decision curve analysis (DCA) were used to assess the performance of the nomogram. The nomogram was finally utilized to stratify patients into low-, intermediate-, and high-risk groups, aiming to assess its efficacy in precisely discerning individuals with diverse overall survival outcomes. Results Alcohol drinking, tumor number, globulin (Glob) and prealbumin (Palb) were identified and integrated to establish a novel prognostic nomogram. The nomogram exhibited strong discriminative ability with C-indices of 0.723 (training cohort) and 0.693 (validation cohort), along with significant Area Under the Curve (AUC) values for 3-year, 5-year, and 8-year OS in both cohorts (0.758, 0.770, and 0.811 for training cohort; 0.744, 0.699 and 0.737 for validation cohort). Calibration plots substantiated its consistency, while DCA curves corroborated its clinical utility. The nomogram further demonstrated exceptional effectiveness in discerning distinct risk populations, highlighting its robust applicability for prognostic stratification. Conclusion Our study successfully developed and validated a robust nomogram model based on four key clinical parameters for predicting 3-, 5- and 8-year OS among elderly cirrhotic HCC patients following ablation therapy. The nomogram exhibited a remarkable capability in identifying high-risk patients, furnishing clinicians with invaluable insights for postoperative surveillance and tailored therapeutic interventions.
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Affiliation(s)
- Wenying Qiao
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Beijing Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Shugui Sheng
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Beijing Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Junnan Li
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Beijing Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Ronghua Jin
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Beijing Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
| | - Caixia Hu
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, People’s Republic of China
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Qiao W, Fan Z, Wang Q, Jin R, Hu C. Development and Validation of a Nomogram to Predict the Recurrence of HCC Patients Undergoing CECT After Ablation. J Hepatocell Carcinoma 2024; 11:65-79. [PMID: 38235069 PMCID: PMC10793121 DOI: 10.2147/jhc.s441540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 01/09/2024] [Indexed: 01/19/2024] Open
Abstract
Purpose We first aimed to compare the prognostic difference between the application of Contrast-enhanced computed tomography (CECT) and Non-enhanced computed tomography (NECT) in hepatocellular carcinoma(HCC) patients with early-stage immediately after ablation. We secondly propose to explore the risk factors for recurrence in patients undergoing CECT, and then develop a nomogram. Patients and Methods Clinical data were collected from 711 patients who received TACE combined with ablation from January 1, 2015, to December 31, 2022, at Beijing Youan Hospital. According to the imaging methods applied after ablation, patients were categorized into the CECT group and the NECT group and then were compared by Kaplan-Meier (KM) curves. Lasso regression is used to screen risk factors for recurrence and the nomogram was plotted. Finally, discrimination, calibration plot, and decision curve analysis (DCA) were used to measure the performance of the nomogram. Results The KM curve indicates that recurrence-free survival (RFS) was longer in the CECT group than in the NECT group (HR =0.759, 95% CI 0.606-0.951, P=0.016). Six variables were selected to construct the nomogram. 1-, 3-, and 5-year area under the curves (AUCs) (0.867, 0.731, 0.773 and 0.896, 0.784, 0.773) of the training and validation cohorts proved the good predictive performance of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classify of patients into three groups according to the risk of recurrence: low risk, intermediate risk, and high risk. There was a statistically significant difference in RFS between the two groups in the training and validation cohorts (P<0.001). Conclusion We demonstrated that HCC patients who underwent CECT evaluation after ablation had a better prognosis, making this evaluation method highly recommended for guiding clinical management.
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Affiliation(s)
- Wenying Qiao
- Interventional Therapy Center for Oncology, Beijing Youan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
| | - Zibo Fan
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Qi Wang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Ronghua Jin
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
| | - Caixia Hu
- Interventional Therapy Center for Oncology, Beijing Youan Hospital, Capital Medical University, Beijing, People’s Republic of China
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Li Z, Song L, Qin B, Li K, Shi Y, Wang H, Wang H, Ma N, Li J, Wang J, Li C. A predictive nomogram for surgical site infection in patients who received clean orthopedic surgery: a retrospective study. J Orthop Surg Res 2024; 19:38. [PMID: 38183110 PMCID: PMC10770936 DOI: 10.1186/s13018-023-04473-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 12/14/2023] [Indexed: 01/07/2024] Open
Abstract
BACKGROUND Surgical site infection (SSI) is a common and serious complication of elective clean orthopedic surgery that can lead to severe adverse outcomes. However, the prognostic efficacy of the current staging systems remains uncertain for patients undergoing elective aseptic orthopedic procedures. This study aimed to identify high-risk factors independently associated with SSI and develop a nomogram prediction model to accurately predict the occurrence of SSI. METHODS A total of 20,960 patients underwent elective clean orthopedic surgery in our hospital between January 2020 and December 2021, of whom 39 developed SSI; we selected all 39 patients with a postoperative diagnosis of SSI and 305 patients who did not develop postoperative SSI for the final analysis. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. Univariate and multivariate logistic regression analyses were conducted in the training cohort to screen for independent risk factors of SSI, and a nomogram prediction model was developed. The predictive performance of the nomogram was compared with that of the National Nosocomial Infections Surveillance (NNIS) system. Decision curve analysis (DCA) was used to assess the clinical decision-making value of the nomogram. RESULTS The SSI incidence was 0.186%. Univariate and multivariate logistic regression analysis identified the American Society of Anesthesiology (ASA) class (odds ratio [OR] 1.564 [95% confidence interval (CI) 1.029-5.99, P = 0.046]), operative time (OR 1.003 [95% CI 1.006-1.019, P < 0.001]), and D-dimer level (OR 1.055 [95% CI 1.022-1.29, P = 0.046]) as risk factors for postoperative SSI. We constructed a nomogram prediction model based on these independent risk factors. In the training and validation cohorts, our predictive model had concordance indices (C-indices) of 0.777 (95% CI 0.672-0.882) and 0.732 (95% CI 0.603-0.861), respectively, both of which were superior to the C-indices of the NNIS system (0.668 and 0.543, respectively). Calibration curves and DCA confirmed that our nomogram model had good consistency and clinical predictive value, respectively. CONCLUSIONS Operative time, ASA class, and D-dimer levels are important clinical predictive indicators of postoperative SSI in patients undergoing elective clean orthopedic surgery. The nomogram predictive model based on the three clinical features demonstrated strong predictive performance, calibration capabilities, and clinical decision-making abilities for SSI.
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Affiliation(s)
- Zhi Li
- Department of Infection Management, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China
| | - Lihua Song
- Department of Infection Management, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China
| | - Baoju Qin
- Department of Infection Management, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China
| | - Kun Li
- Department of Infection Management, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China
| | - Yingtao Shi
- Operating Room, Xingtai General Hospital of North China Medical and Health Group, Xingtai, Hebei, China
| | - Hongqing Wang
- Department of Orthopedics, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China
| | - Huiwang Wang
- Department of Orthopedics, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China
| | - Nan Ma
- Department of Orthopedics, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China
| | - Jinlong Li
- Hebei Provincial Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China
| | - Jitao Wang
- Hebei Provincial Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China.
| | - Chaozheng Li
- Department of Infection Management, North China Healthcare Group Xingtai General Hospital, Xingtai, Hebei, China.
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