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Ma Z, Yang S, Yang Y, Luo J, Zhou Y, Yang H. Development and validation of prediction models for the prognosis of colon cancer with lung metastases: a population-based cohort study. Front Endocrinol (Lausanne) 2023; 14:1073360. [PMID: 37583430 PMCID: PMC10424923 DOI: 10.3389/fendo.2023.1073360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 04/20/2023] [Indexed: 08/17/2023] Open
Abstract
Background Current studies on the establishment of prognostic models for colon cancer with lung metastasis (CCLM) were lacking. This study aimed to construct and validate prediction models of overall survival (OS) and cancer-specific survival (CSS) probability in CCLM patients. Method Data on 1,284 patients with CCLM were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly assigned with 7:3 (stratified by survival time) to a development set and a validation set on the basis of computer-calculated random numbers. After screening the predictors by the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, the suitable predictors were entered into Cox proportional hazard models to build prediction models. Calibration curves, concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were used to perform the validation of models. Based on model-predicted risk scores, patients were divided into low-risk and high-risk groups. The Kaplan-Meier (K-M) plots and log-rank test were applied to perform survival analysis between the two groups. Results Building upon the LASSO and multivariate Cox regression, six variables were significantly associated with OS and CSS (i.e., tumor grade, AJCC T stage, AJCC N stage, chemotherapy, CEA, liver metastasis). In development, validation, and expanded testing sets, AUCs and C-indexes of the OS and CSS prediction models were all greater than or near 0.7, which indicated excellent predictability of models. On the whole, the calibration curves coincided with the diagonal in two models. DCA indicated that the models had higher clinical benefit than any single risk factor. Survival analysis results showed that the prognosis was worse in the high-risk group than in the low-risk group, which suggested that the models had significant discrimination for patients with different prognoses. Conclusion After verification, our prediction models of CCLM are reliable and can predict the OS and CSS of CCLM patients in the next 1, 3, and 5 years, providing valuable guidance for clinical prognosis estimation and individualized administration of patients with CCLM.
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Affiliation(s)
| | | | | | | | | | - Huiyong Yang
- School of Medicine, Huaqiao University, Quanzhou, China
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Zhang Y, Zhang Z, Wei L, Wei S. Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer. Front Public Health 2022; 10:1008137. [PMID: 36605237 PMCID: PMC9810140 DOI: 10.3389/fpubh.2022.1008137] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
Purpose The purpose of this study was to investigate the clinical and non-clinical characteristics that may affect the early death rate of patients with metastatic colorectal carcinoma (mCRC) and develop accurate prognostic predictive models for mCRC. Method Medical records of 35,639 patients with mCRC diagnosed from 2010 to 2019 were obtained from the SEER database. All the patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. X-tile software was utilized to identify the optimal cutoff point for age and tumor size. Univariate and multivariate logistic regression models were used to determine the independent predictors associated with overall early death and cancer-specific early death caused by mCRC. Simultaneously, predictive and dynamic nomograms were constructed. Moreover, logistic regression, random forest, CatBoost, LightGBM, and XGBoost were used to establish machine learning (ML) models. In addition, receiver operating characteristic curves (ROCs) and calibration plots were obtained to estimate the accuracy of the models. Decision curve analysis (DCA) was employed to determine the clinical benefits of ML models. Results The optimal cutoff points for age were 58 and 77 years and those for tumor size of 45 and 76. A total of 15 independent risk factors, namely, age, marital status, race, tumor localization, histologic type, grade, N-stage, tumor size, surgery, radiation, chemotherapy, bone metastasis, brain metastasis, liver metastasis, and lung metastasis, were significantly associated with the overall early death rate of patients with mCRC and the cancer-specific early death rate of patients with mCRC, following which nomograms were constructed. The ML models revealed that the random forest model accurately predicted outcomes, followed by logistic regression, CatBoost, XGBoost, and LightGBM models. Compared with other algorithms, the random forest model provided more clinical benefits than other models and can be used to make clinical decisions in overall early death and specific early death caused by mCRC. Conclusion ML algorithms combined with nomograms may play an important role in distinguishing early deaths owing to mCRC and potentially help clinicians make clinical decisions and follow-up strategies.
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Affiliation(s)
- Yalong Zhang
- Department of Ultrasound Medicine, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zunni Zhang
- Department of Clinical Laboratory, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Liuxiang Wei
- Department of Ultrasound Medicine, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Shujing Wei
- Department of Ultrasound Medicine, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, China,*Correspondence: Shujing Wei ✉
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Tai Q, Xue W, Li M, Zhuo S, Zhang H, Fang F, Zhang J. Survival Nomogram for Metastasis Colon Cancer Patients Based on SEER Database. Front Genet 2022; 13:832060. [PMID: 35222547 PMCID: PMC8864078 DOI: 10.3389/fgene.2022.832060] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 01/13/2022] [Indexed: 12/20/2022] Open
Abstract
Introduction: A prediction model for the 1-, 3-, and 5-year survival rates of metastatic colon cancer (mCC) patients was developed by analyzing important risk factors for the prognosis of mCC patients based on the SEER database. Method: The characteristic of 10,946 patients diagnosed with mCC between 2010 and 2015 was obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio. Univariate and multivariate cox for independent predictors of mCC prognosis were performed, and nomogram was constructed. The accuracy of the model was verified by calibration curves, ROC curves, and C-index, and the clinical utility of the model was analyzed using decision analysis curves. Result: Age, primary site, grade, surgery, and other eight factors were significantly associated with the prognosis of mCC patients, and these predictors were included in the construction of the nomogram. The C-index was 0.731 (95% CI 0.725–0.737) and 0.736 (95% CI 0.726–0.746) for the training cohort and the validation set, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.7 for both the training cohort and the validation set at 1, 3, and 5 years. Conclusion: The constructed prediction model had an excellent predictive accuracy, which will help clinical decision-making of mCC patients after surgery and individualized treatment.
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Affiliation(s)
- Qinwen Tai
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
- *Correspondence: Qinwen Tai, ; Jinhui Zhang,
| | - Wei Xue
- Department of Pharmacy, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, China
| | - Mengying Li
- The First College of Clinical Science, Anhui Medical University, Hefei, China
| | - Shuli Zhuo
- Medical College of Shaoguan University, Shaoguan, China
| | - Heng Zhang
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Fa Fang
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Jinhui Zhang
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
- *Correspondence: Qinwen Tai, ; Jinhui Zhang,
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Lemini R, Attwood K, Almerey T, Gunn J, Yeager TE, Elias AW, Partain K, Jorgensen MS, Ji W, Gabriel EM, Colibaseanu DT. Is metastasectomy a worthy option?-the role of surgery in metastatic colon cancer to liver and lungs. J Gastrointest Oncol 2019; 10:1032-1048. [PMID: 31949921 DOI: 10.21037/jgo.2019.09.06] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Background The role of surgery and metastasectomy is controversial in the treatment of stage IV colon cancer (CC). The aim of this study was to investigate the relationship between primary tumor resection (PTR) with metastasectomy and survival in patients diagnosed with metastatic CC. Methods The National Cancer Data Base (NCDB) was retrospectively queried for patients diagnosed with colon adenocarcinoma from 2004 to 2013. Patient demographics, clinical characteristics, and short-term outcomes were collected. Groups were generated based on if surgery was performed and, if so, was metastasectomy involved. Associations between groups were evaluated using Kruskal-Wallis and Pearson Chi-square tests. Overall survival (OS) was summarized using standard Kaplan-Meier methods. The association between surgical group and OS was evaluated using the log-rank test. Results Of 31,172 patients, 13,214 (42.4%) had surgery while 17,958 (57.6%) did not. Among these, 81.3% of patients had liver metastases only, while 18.7% of patients had both liver and lung metastases. Median OS was 15.1 months (95% CI: 14.8 to 15.5 months) for the entire cohort. However, median OS was significantly better for those who had surgery (either PTR alone or PTR with metastasectomy) compared to those who did not (21.8 vs. 7.5 months, P<0.001). Patients who received PTR with metastasectomy had worse median OS (20.5 vs. 21.8 months, P=0.035) compared to those who only received PTR (P=0.211). Conclusions PTR in select patients diagnosed with metastatic CC provides a remarkable improvement to survival rate. The role of metastasectomy remains controversial as no difference in survival outcomes exists between patients who received it and who did not.
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Affiliation(s)
- Riccardo Lemini
- Department of Surgery, Division of Colon and Rectal Surgery, Mayo Clinic, Jacksonville, FL, USA
| | - Kristopher Attwood
- Department of Biostatistics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Tariq Almerey
- Department of Surgery, Mayo Clinic, Jacksonville, FL, USA
| | - Jinny Gunn
- Department of Surgery, Mayo Clinic, Jacksonville, FL, USA
| | | | | | | | | | - Wenyan Ji
- Department of Biostatistics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Emmanuel M Gabriel
- Department of Surgery, Division of Surgical Oncology, Mayo Clinic, Jacksonville, FL, USA
| | - Dorin T Colibaseanu
- Department of Surgery, Division of Colon and Rectal Surgery, Mayo Clinic, Jacksonville, FL, USA
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Ahmed S, Pahwa P, Fields A, Chandra-Kanthan S, Iqbal N, Zaidi A, Reeder B, Plaza FA, Zhu T, Leis A. Predictive Factors of the Use of Systemic Therapy in Stage IV Colorectal Cancer: Who Gets Chemotherapy? Oncology 2015; 88:289-97. [DOI: 10.1159/000368245] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2014] [Accepted: 08/25/2014] [Indexed: 11/19/2022]
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Nielsen HJ, Jess P, Aldulaymi BH, Jørgensen LN, Laurberg S, Nielsen KT, Madsen MR, Brünner N, Christensen IJ. Early detection of recurrence after curative resection for colorectal cancer - obstacles when using soluble biomarkers? Scand J Gastroenterol 2013; 48:326-33. [PMID: 23324066 DOI: 10.3109/00365521.2012.758774] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
OBJECTIVE Results from monitoring studies using biomarkers in blood samples aiming at early detection of recurrent colorectal cancer (CRC) are presently evaluated. However, some serological biomarker levels are influenced by the surgical trauma, which may complicate translation of the levels in relation to recurrence. The primary purpose of the present study was to evaluate the frequency of postoperative surgical interventions during a follow-up period of patients who have undergone surgery for primary CRC. METHODS In a prospective multicenter, clinical study, 634 patients resected for primary CRC were followed in the outpatient clinic every third month. Blood samples were drawn at each visit. A subgroup of 165 stage II and III patients, who had been followed for at least 3 years, was selected. Any recent surgical intervention associated with the primary disease and/or other diseases were recorded at each visit to the outpatient clinic. RESULTS Among the 165 patients, 49 developed recurrence (R+), 107 did not (R-) and 11 developed a new primary cancer, including 2 in the R+ group. Within the 3 years of observation, 78 (47.3%) of the 165 patients underwent 117 (range 1-5) postoperative surgical interventions. Seventy-five operations were related to CRC and 42 to benign diseases, while none were related to a new primary, malignant disease. CONCLUSION Patients resected for CRC are frequently undergoing surgical procedures in the postoperative follow-up period. Therefore, postoperative monitoring using soluble biomarker levels, which may be influenced by the surgical trauma, must be adjusted in relation to postoperative surgical interventions.
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Affiliation(s)
- Hans Jørgen Nielsen
- Department of Surgical Gastroenterology 360, Hvidovre Hospital, Hvidovre, Denmark.
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Nielsen HJ, Brünner N. Scandinavian Journal of Gastroenterology. Editorial. Scand J Gastroenterol 2012; 47:256-7. [PMID: 22182370 DOI: 10.3109/00365521.2012.640827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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Kanthan R, Senger JL, Ahmed S, Kanthan S. Recent Advances in the Management of Stage IV Colon Cancer. ACTA ACUST UNITED AC 2012. [DOI: 10.4236/jct.2012.36145] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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