Clinicopathological factors associated with synchronous distant metastasis and prognosis of stage T1 colorectal cancer patients

Li, Qiken; Wang, Gang; Luo, Jun; Li, Bo; Chen, Weiping

doi:10.1038/s41598-021-87929-x

Cited by 11 publications

(8 citation statements)

References 35 publications

(14 reference statements)

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“…(10,(20)(21)(22)(23)(24) As Saadati et al (10) and Hassan et al (23) reported, sex was a prognostic factor in colorectal cancers both in Iran and Malaysia, but in the majority of studies, sex did not have a prognostic value. (20,(25)(26)(27) We did not find a significant relationship between sex and mortality either; yet the incidence was higher in men than in women, with a male: female ratio of 1.31. This was similar to previous reports from East Azerbaijan, (8) Iran (15) and the world.…”

Section: Discussioncontrasting

confidence: 60%

Epidemiological aspects of colorectal cancer in East Azerbaijan, Northwest Iran: five year survival analysis

et al. 2021

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BackgroundColorectal cancer (CRC) is the third most common cancer and the second leading cause of death from cancer in the world. Currently, CRC is the fourth most common cancer in men and the second common cancer in women of all ages in Iran. The aim of this study was to determine the epidemiologic profile of CRC along with CRC specific survival analysis. MethodsThis was an analytical cross-sectional study using the East Azerbaijan Population Based Cancer Registry database (EA-PBCR) as a source for data related to patients with a diagnosis of CRC. Colorectal cancer specific 1- to 5-year survival analysis and mortality rates were calculated. Log-rank test and Cox regression analysis was performed to test the equality of survival function and mortality hazard. ResultsA total of 2,366 newly diagnosed CRCs were registered during 3 years, with a male: female ratio of 1.31. Overall survival rate was 49.8%. One- to 5-year survival rates were 96.21%, 56.94%, 48.62%, 47.88% and 46.76% respectively. At multivariate level, after adjusting for all variables, regression analysis showed that the hazard of mortality in stage IV cancers was 46.44 times higher than that in stage I cancers (HR=46.44, 95% CI: 14.86-145.14, p=0.000). However, differences in patients’ age group and sex and the subsite of cancer did not create any statistically significant variation between groups in regards to mortality hazards (p>0.05). ConclusionThis study demonstrated that the stage and grade of CRC were important prognostic factors and that early screening and diagnosis of CRC were essential.

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Section: Discussioncontrasting

confidence: 60%

Epidemiological aspects of colorectal cancer in East Azerbaijan, Northwest Iran: five year survival analysis

et al. 2021

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“…They also found that synchronous LM was an independent prognostic factor for CRC patients. Analogously, Li et al [ 56 ] employed the SEER database to construct a T1 CRC all distant metastasis model by virtue of the conventional logistic regression. Howbeit, due to the limitation of the algorithm and the approach to process data, they acquired a passable model (AUC = 0.879) with ineluctable overfitting.…”

Section: Discussionmentioning

confidence: 99%

Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

Han

Jun

Chen³

et al. 2022

Cancer Cell Int

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Background Liver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. Nevertheless, there is still no effective model to predict the risk of LM in T1 CRC patients. Hence, we aim to construct an accurate predictive model and an easy-to-use tool clinically. Methods We integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER, training dataset) and Xijing hospital (testing dataset). Artificial intelligence (AI) and machine learning (ML) methods were adopted to establish the predictive model. Results A total of 16,785 and 326 T1 CRC patients from SEER database and Xijing hospital were incorporated respectively into the study. Every single ML model demonstrated great predictive capability, with an area under the curve (AUC) close to 0.95 and a stacking bagging model displaying the best performance (AUC = 0.9631). Expectedly, the stacking model exhibited a favorable discriminative ability and precisely screened out all eight LM cases from 326 T1 patients in the outer validation cohort. In the subgroup analysis, the stacking model also demonstrated a splendid predictive ability for patients with tumor size ranging from one to50mm (AUC = 0.956). Conclusion We successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in the external dataset. Ultimately, we designed a novel and easy-to-use decision tree, which only incorporated four fundamental parameters and could be successfully applied in clinical practice.

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“…A similar trend was observed for metastases in the lungs; those patients with metastases in the lungs have four times the risk of death compared to those without metastases to another site. A study by Li, Wang [ 37 ] revealed that the liver is the most affected metastasis site for patients with CRC, and they exhibited the poorest survival outcome. The anatomical situation of the liver and its portal circulation serves as a vital confluence for metastasis and recurrence routes for advancing tumours such as CRC.…”

Section: Discussionmentioning

confidence: 99%

The Prediction of Survival Outcome and Prognosis Factor in Association with Comorbidity Status in Patients with Colorectal Cancer: A Research-Based Study

et al. 2022

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Colorectal carcinoma (CRC) is rising exponentially in Asia, representing 11% of cancer worldwide. This study analysed the influence of CRC on patients’ life expectancy (survival and prognosis factors) via clinicopathology data and comorbidity status of CRC patients. Methodology: A retrospective study performed in HUSM using clinical data from the Surgery unit from 2015 to 2020. The demographic and pertinent clinical data were retrieved for preliminary analyses (data cleansing and exploration). Demographics and pathological characteristics were illustrated using descriptive analysis; 5-year survival rates were calculated using Kaplan–Meier methods; potential prognostic variables were analysed using simple and multivariate logistic regression analysis conducted via the Cox proportional hazards model, while the Charlson Comorbidity Scale was used to categorize patients’ disease status. Results: Of a total of 114 CRC patients, two-thirds (89.5%) were from Malay tribes, while Indian and Chinese had 5.3% each. The 50–69.9 years were the most affected group (45.6%). Overall, 40.4% were smokers (majorly male (95.7%)), 14.0% ex-smokers, and 45.6% non-smokers (p-value = 0.001). The Kaplan–Meier overall 5-year median survival time was 62.5%. From the outcomes, patients who were male and >70 years had metastasis present, who presented with per rectal bleeding and were classified as Duke C; and who has tumour in the rectum had the lowest survival rate. Regarding the prognosis factors investigated, “Gender” (adjusted hazard ratio (HR): 2.62; 95% CI: 1.56–7.81, p-value = 0.040), “Presence of metastases” (HR: 3.76; 95% CI: 1.89–7.32, p-value = 0.010), “Metastasis site: Liver” (HR: 5.04; 95% CI: 1.71–19.05, p-value = 0.039), “Lymphovascular permeation” (HR: 2.94; 95% CI: 1.99–5.92, p-value = 0.021), and “CEA-level” (HR: 2.43; 95% CI: 1.49–5.80, p-value = 0.001) remained significant in the final model for multiple Cox proportional hazard regression analyses. There was a significant mean association between tumour grades and the patient’s comorbidity status. Conclusions: Histopathological factors (gender, metastases presence, site of metastases, CEA level, and lymphovascular permeation) showed the best prognosis-predicting factors in CRC.

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Clinicopathological factors associated with synchronous distant metastasis and prognosis of stage T1 colorectal cancer patients

Cited by 11 publications

References 35 publications

Epidemiological aspects of colorectal cancer in East Azerbaijan, Northwest Iran: five year survival analysis

Epidemiological aspects of colorectal cancer in East Azerbaijan, Northwest Iran: five year survival analysis

Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

The Prediction of Survival Outcome and Prognosis Factor in Association with Comorbidity Status in Patients with Colorectal Cancer: A Research-Based Study

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