Dataset Information

Second Primary Malignancies in Patients with Colorectal Cancer: A Population-Based Analysis.

ABSTRACT:

Purpose

This study aimed to profile the characteristics of patients with colorectal cancer (CRC) with a second primary malignancy (SPM) and to identify patients with CRC at high risk of developing SPMs.

Methods

We retrospectively reviewed data on patients with CRC aged 20-79?years from the Surveillance, Epidemiology, and End Results (SEER) database. Eligible patients were categorized into only one primary malignancy and SPM cohorts. A competing-risk model was used to quantify associations between SPM occurrence and the multiple traits of patients. Finally, a decision curve analysis (DCA) was used to evaluate the clinical usefulness of the model by calculating net benefit.

Results

A total of 179,884 patients were identified, 18,285 (10.2%) of whom developed SPMs during a maximum follow-up of approximately 18?years. The median survival time after the second diagnosis was less than 4?years. The 3-year, 5-year, and 10-year cumulative risks of developing an SPM were 3.9%, 5.9%, and 10.0%, respectively. According to the multivariable competing-risk model, male colon cancer survivors, older in age, with a well-differentiated tumor and localized disease, who were treated with surgery were susceptible to SPMs. The DCA yielded a wide range of risk thresholds at which the net benefits would be obtained from our proposed model.

Conclusion

CRC survivors remain at high risk of developing SPMs. Patients with a second diagnosis of cancer showed not only significantly worse survival but also higher cancer-specific mortality. A web-based individualized predictive tool was also provided to assist clinicians in identifying patients at high risk of developing SPMs and planning their future care management.

Implications for practice

Colorectal cancer survivors remain at high risk of developing a second primary malignancy (SPM). This study aimed to profile the characteristics of patients with colorectal cancer with second primary malignancies and to further explore the risk factors related to the development of second primary malignancies, using a large population-based cohort. A clinically useful competing-risk nomogram was developed to predict the risk of SPMs based on individual clinical factors. According to the findings, older age, male sex, white or black race, localized disease, and treatment with surgery among patients with colon cancer were associated with an increased risk of developing an SPM. These findings and the proposed tool could be useful to clinicians and caregivers in the clinical counseling of patients with colorectal cancer and the development of long-term care management.

SUBMITTER: Jia H

PROVIDER: S-EPMC7160402 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Publications

Second Primary Malignancies in Patients with Colorectal Cancer: A Population-Based Analysis.

Jia Huixun H Li Qingguo Q Yuan Jing J Sun Xiaodong X Wu Zhenyu Z

The oncologist 20200114 4

<h4>Purpose</h4>This study aimed to profile the characteristics of patients with colorectal cancer (CRC) with a second primary malignancy (SPM) and to identify patients with CRC at high risk of developing SPMs.<h4>Methods</h4>We retrospectively reviewed data on patients with CRC aged 20-79 years from the Surveillance, Epidemiology, and End Results (SEER) database. Eligible patients were categorized into only one primary malignancy and SPM cohorts. A competing-risk model was used to quantify asso ...[more]

PMID: 31943509

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Project description:BackgroundSecond primary malignancy (SPM) is becoming a threat for the health of cancer survivors. However, data on the features and results of patients with hepatocellular carcinoma (HCC) with SPMs are scarce. This study aimed to explore the characteristics of HCC patients with SPMs and to screen HCC patients who are at a high risk of developing SPMs.MethodHCC patients diagnosed between 2000 and 2014 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively analyzed. Eligible patients were divided into the only one primary malignancy and SPM groups. The Fine-Gray proportional subdistribution hazards model was used to explore the risk factors of developing SPMs, and a competing-risk model was established to predict the probability of developing SPMs for HCC patients after initial diagnosis. The calibration curves, concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram.ResultsA total of 40,314 HCC patients were identified, 1,593 (3.95%) of whom developed SPMs 2 months after the initial diagnosis with a maximum follow-up time of approximately 18 years. The 3-, 5-, and 10-year cumulative incidence of SPMs were 2.35%, 3.12%, and 4.51%, respectively. Age at initial diagnosis, extent of disease, tumor size, and treatment were identified as the independent risk factors of developing SPMs and integrated into the competing-risk nomogram. The C-index of the nomogram was 0.677 (95% confidence interval 0.676-0.678), and the calibration curves showed an excellent agreement between the nomogram prediction and the actual observations. Furthermore, DCA indicated that the nomogram had good net benefits in clinical scenarios.ConclusionsHCC survivors remain at a high risk of developing SPMs. The development of SPMs was associated with the clinical features and treatment strategies. A competing-risk nomogram was constructed to help surgeons identify the patients who are at a high risk of developing SPMs and contribute to the further management of SPMs.

Project description:Background: Previous studies have revealed an increased risk of second primary malignancies (SPMs) after colorectal cancer (CRC); however, no previous investigation has quantified differences in the risk of SPMs based on the histological subtypes of first primary CRC. Methods: Patients diagnosed with first primary CRC between 2000 and 2011 were identified from the Surveillance, Epidemiology, and End Results cancer registries. The patients were divided into three cohorts: classical adenocarcinoma (CA), mucinous adenocarcinoma (MA), and signet-ring cell carcinoma (SRCC). Standardized incidence ratios were calculated to assess the risk of SPMs among the patients. Results: Overall risk of SPMs was significantly higher among patients with three histological subtypes of CRC than in the general population. The risk of esophagus cancer was significantly increased in SRCC. The risk of small intestine, colon and rectum, and corpus uteri cancers was high in three histological subtypes, with the highest risk observed in SRCC, followed by MA. Increased risks of second stomach, uterus, urinary bladder, kidney, and thyroid cancers were only observed in CA patients, while increased risk of second renal pelvis cancer was limited to MA patients. Furthermore, the high overall risk of SPMs in CA patients persisted regardless of clinicopathological factors. After surgery combined with chemotherapy treatment, CA patients were more prone to developing second small intestine, colon and rectum cancers than those treated with surgery only. A lower second prostate cancer risk was observed in rectal CA patients treated with surgery combined with radiotherapy than in patients treated with surgery only. Conclusion: The present study revealed that the risk of developing SPMs after CRC varied based on the histological subtypes of the first primary CRC. Although the mechanisms underlying the observed patterns of SPM risk remain unknown, the study provided insights into future cancer surveillance based on the histological subtypes of CRC.

Project description:Background The most common form of treatment for non-metastatic lung cancer is surgery-based combination therapy, which may also include adjuvant radiotherapy or chemotherapy. Second primary malignancies (SPMs) are uncommon but significant radiation side effects in patients with resectable lung cancer, and SPMs have not been adequately investigated. Our study aims to assess the correlations of radiotherapy with the development of SPMs in patients with resectable lung cancer. Methods We screened for any primary malignancy that occurred more than five years after the diagnosis of resectable lung cancer. Based on the large cohort of the Surveillance, Epidemiology and End Results database, radiotherapy-correlated risks were estimated using the Poisson regression analysis and the cumulative incidence of SPMs was calculated using Fine-Gray competing risk regression analysis. Results Among the 62,435 patients with non-metastatic lung cancer undergoing surgery, a total of 11,341 (18.16%) patients have received radiotherapy. Our findings indicated that radiotherapy was substantially related to a high risk of main second solid malignancies (RR = 1.21; 95%CI, 1.08 to 1.35) and a negligible risk of main second hematologic malignancies (RR = 1.08; 95%CI, 0.84 to 1.37). With the greatest number of patients, the risk of acquiring a second primary gastrointestinal cancer was the highest overall (RR = 1.77; 95 percent CI, 1.44 to 2.15). The cumulative incidence and standardized incidence ratios of SPMs revealed similar findings. Furthermore, the young and the elderly may be more vulnerable, and the highest risk of acquiring most SPMs was seen more than ten years after lung cancer diagnosis. Additionally, more attention should be paid to the second primary gastrointestinal cancer in young individuals with resectable lung cancer. Conclusion After receiving radiotherapy, an increased risk of developing second primary solid and gastrointestinal cancers was observed for patients with resectable lung cancer. The prevention of SPMs associated with radiotherapy requires further attention. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03857-y.

Dataset Information

Second Primary Malignancies in Patients with Colorectal Cancer: A Population-Based Analysis.

Purpose

Methods

Results

Conclusion

Implications for practice

Publications

Second Primary Malignancies in Patients with Colorectal Cancer: A Population-Based Analysis.

Similar Datasets

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