Association of Age and Overall Survival in Surgically Resected Colorectal Cancer Patients

Lewis, Samara E.; Stewart, Kenneth E.; Garwe, Tabitha; Sarwar, Zoona; Morris, Katherine T.

doi:10.1016/j.jss.2022.08.031

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…Shimomura’s study concluded that adequate lymph node examination is essential to ensure the prognostic value of the lymph node ratio in patients with stage III colorectal cancer [ 19 ]. Lewis et al found that older patients diagnosed with stage I or II disease had worse overall survival, but at higher stages of the disease, overall survival for all age groups was similar [ 20 ]. Krajc et al demonstrated that marriage was associated with significantly higher overall survival, while unmarried men were associated with significantly lower survival rates, marital status should be considered when providing cancer care [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Conditional survival analysis and real-time prognosis prediction in stage III T3–T4 colon cancer patients after surgical resection: a SEER database analysis

Zeng,

Xue,

Chen

et al. 2024

Int J Colorectal Dis

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Background Conditional survival (CS) takes into consideration the duration of survival post-surgery and can provide valuable additional insights. The aim of this study was to investigate the risk factors associated with reduced one-year postoperative conditional survival in patients diagnosed with stage III T3–T4 colon cancer and real-time prognosis prediction. Furthermore, we aim to develop pertinent nomograms and predictive models. Methods Clinical data and survival outcomes of patients diagnosed with stage III T3–T4 colon cancer were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, covering the period from 2010 to 2019. Patients were divided into training and validation cohorts at a ratio of 7:3. The training set consisted of a total of 11,386 patients for conditional overall survival (cOS) and 11,800 patients for conditional cancer-specific survival (cCSS), while the validation set comprised 4876 patients for cOS and 5055 patients for cCSS. Univariate and multivariate Cox regression analyses were employed to identify independent risk factors influencing one-year postoperative cOS and cCSS. Subsequently, predictive nomograms for cOS and cCSS at 2-year, 3-year, 4-year, and 5-year intervals were constructed based on the identified prognostic factors. The performance of these nomograms was rigorously assessed through metrics including the concordance index (C-index), calibration curves, and the area under curve (AUC) derived from the receiver operating characteristic (ROC) analysis. Clinical utility was further evaluated using decision curve analysis (DCA). Results A total of 18,190 patients diagnosed with stage III T3–T4 colon cancer were included in this study. Independent risk factors for one-year postoperative cOS and cCSS included age, pT stage, pN stage, pretreatment carcinoembryonic antigen (CEA) levels, receipt of chemotherapy, perineural invasion (PNI), presence of tumor deposits, the number of harvested lymph nodes, and marital status. Sex and tumor site were significantly associated with one-year postoperative cOS, while radiation therapy was notably associated with one-year postoperative cCSS. In the training cohort, the developed nomogram demonstrated a C-index of 0.701 (95% CI, 0.711–0.691) for predicting one-year postoperative cOS and 0.701 (95% CI, 0.713–0.689) for one-year postoperative cCSS. Following validation, the C-index remained robust at 0.707 (95% CI, 0.721–0.693) for one-year postoperative cOS and 0.700 (95% CI, 0.716–0.684) for one-year postoperative cCSS. ROC and calibration curves provided evidence of the model's stability and reliability. Furthermore, DCA underscored the nomogram’s superior clinical utility. Conclusions Our study developed nomograms and predictive models for postoperative stage III survival in T3–T4 colon cancer with the aim of accurately estimating conditional survival. Survival bias in our analyses may lead to overestimation of survival outcomes, which may limit the applicability of our findings.

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Section: Discussionmentioning

confidence: 99%

Conditional survival analysis and real-time prognosis prediction in stage III T3–T4 colon cancer patients after surgical resection: a SEER database analysis

Zeng,

Xue,

Chen

et al. 2024

Int J Colorectal Dis

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Conditional survival analysis and real-time prognosis prediction in stage III T3-T4 colon cancer patients after surgical resection: a SEER database analysis

Zeng,

Xue,

Chen

et al. 2023

Preprint

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Background Conditional survival (CS) takes into consideration the duration of survival post-surgery and can provide valuable additional insights. The aim of this study was to investigate the risk factors associated with reduced one-year postoperative conditional survival in patients diagnosed with stage III T3-T4 colon cancer and real-time prognosis prediction. Furthermore, we aim to develop pertinent nomograms and predictive models. Methods Clinical data and survival outcomes of patients diagnosed with stage III T3-T4 colon cancer were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, covering the period from 2010 to 2019. Patients were divided into training and validation cohorts at a ratio of 7:3. The training set consisted of a total of 11,386 patients for conditional overall survival (cOS) and 11,800 patients for conditional cancer-specific survival (cCSS), while the validation set comprised 4,876 patients for cOS and 5,055 patients for cCSS. Univariate and multivariate Cox regression analyses were employed to identify independent risk factors influencing one-year postoperative cOS and cCSS. Subsequently, predictive nomograms for cOS and cCSS at 2-year, 3-year, 4-year, and 5-year intervals were constructed based on the identified prognostic factors. The performance of these nomograms was rigorously assessed through metrics including the concordance index (C-index), calibration curves, and the area under the curve (AUC) derived from the receiver operating characteristic (ROC) analysis. Clinical utility was further evaluated using decision curve analysis (DCA). Results A total of 18,190 patients diagnosed with stage III T3-T4 colon cancer were included in this study. Independent risk factors for one-year postoperative cOS and cCSS included age, pT stage, pN stage, pretreatment carcinoembryonic antigen (CEA) levels, receipt of chemotherapy, perineural invasion (PNI), presence of tumor deposits, the number of harvested lymph nodes, and marital status. Gender and tumor site were significantly associated with one-year postoperative cOS, while radiation therapy was notably associated with one-year postoperative cCSS. In the training cohort, the developed nomogram demonstrated a C-index of 0.701 (95% CI, 0.711–0.691) for predicting one-year postoperative cOS and 0.701 (95% CI, 0.713–0.689) for one-year postoperative cCSS. Following validation, the C-index remained robust at 0.707 (95% CI, 0.721–0.693) for one-year postoperative cOS and 0.700 (95% CI, 0.716–0.684) for one-year postoperative cCSS. Receiver operating characteristic (ROC) and calibration curves provided evidence of the model's stability and reliability. Furthermore, decision curve analysis (DCA) underscored the nomogram's superior clinical utility. Conclusions Our developed nomogram serves as a precise and a colon cancer essible tool for clinicians to predict the one-year risk of cOS and cCSS in stage III T3-T4 colon cancer patients who have undergone surgery. These findings empower clinicians in formulating informed clinical decisions and effective follow-up strategies.

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Preoperative Albumin to Alkaline Phosphatase Ratio and Inflammatory Burden Index for Rectal Cancer Prognostic Nomogram-Construction: Based on Multiple Machine Learning

Li,

Zhou,

Zhou

et al. 2024

JIR

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Association of Age and Overall Survival in Surgically Resected Colorectal Cancer Patients

Cited by 3 publications

References 30 publications

Conditional survival analysis and real-time prognosis prediction in stage III T3–T4 colon cancer patients after surgical resection: a SEER database analysis

Conditional survival analysis and real-time prognosis prediction in stage III T3–T4 colon cancer patients after surgical resection: a SEER database analysis

Conditional survival analysis and real-time prognosis prediction in stage III T3-T4 colon cancer patients after surgical resection: a SEER database analysis

Preoperative Albumin to Alkaline Phosphatase Ratio and Inflammatory Burden Index for Rectal Cancer Prognostic Nomogram-Construction: Based on Multiple Machine Learning

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