Risk of Second Primary Malignancies in Colon Cancer Patients Treated With Colectomy

Background: Second primary malignancy (SPM) attracts a growing attention. However, the clinical features of colon cancer (CC) survivors with SPMs are not clear and could help guide clinicians to develop a better surveillance strategy. Methods: We reviewed 56,930 CC survivors treated with colectomy from the Surveillance, Epidemiology, and End Results (SEER) database during 1998–2011. Competing risk models and nomograms were conducted for predicting the risk of occurring SPMs. The clinical utility of the models was measured by decision curve analysis (DCA) using net benefit approaches. Results: Five thousand thirteen (17.1%) of male patients developed SPMs and sites of SPMs included prostate (32.2%), lung and bronchus (11.6%), urinary bladder and kidney (10.8%), colon (10.0%), and melanoma of the skin (3.9%), while 3,592 (13.0%) of female patients occurred SPMs and sites of SPMs involved breast (25.8%), lung and bronchus (13.6%), colon (11.6%), uterus (8.2%), urinary bladder, and kidney (5.6%). Survivors with a second carcinoma of lung and bronchus showed the worst prognosis. Older age increased the risk of SPMs in both male (Subdistribution hazard ratio =2.85 [95% confidence interval = 2.53–3.21]) and female (1.80 [1.59–2.04]) survivors, especially for the risk of a second prostate carcinoma in male (5.33 [4.03–7.03]). Compared with white race, black male survivors remained at higher risk to develop the second prostate carcinoma (1.98 [1.74–2.26]). Competing-risk nomograms for CC survivors were established to help clinicians predict the probabilities of overall SPMs and prostate carcinoma. Validation of nomograms showed good discrimination and accuracy, and DCAs revealed the clinical effectiveness. Conclusions: We profiled the clinical characteristics of a large population-based cohort of CC survivors with SPMs. These features may improve future follow-up management, especially for the surveillance of second prostate cancer in men and second breast cancer in women.


INTRODUCTION
Colon cancer (CC) is the most commonly diagnosed digestive malignancy in the world (1,2), and in 2020, it is estimated that it would be 104,610 incident cases in the United States (3). With the development of the early diagnosis, effective treatments and cancer surveillance, there has been seen improved in 5year survival from 49.8 to 66.2% (4), resulting in a continuously increasing number of CC survivors. Unfortunately, it was reported that more than 8% of these survivors were facing the probability of progressing a second primary malignancy (SPM) (5) and SPM becomes one of the main causes of death for those patients (6). Hence, there are a growing number of studies exploring the risk factors of SPM in different cancer survivors such as breast (7), lung (8) as well as colorectal cancer (9,10). However, these studies used logistic regressions or Cox proportional hazard regressions to analyze SPM-related factors, which ignored the death as a competing event for occurring PSMs. They also did not take into account the heterogeneity of SPM risk between colon and rectum, as well as male and female. Additionally, probabilities of SPMs sites and their survivals were less known and the effective nomogram for prediction was not conducted (11,12).
The aim of the present study was to comprehensively characterize male and female CC patients suffering from SPMs, and to find out the survivals and incidence rates of top 5 SPMs sites, using two large population-based cohorts (SPM cohort and only one primary malignancy (OOPM) cohort) from the Surveillance, Epidemiology, and End Results (SEER) database. We first exhibited the differences of demographic variables and tumor characteristics between these two cohorts, and calculated the survival and cumulative incidence of top 5 SPMs sites. Then, the significant unbiased factors were demonstrated to be linked with the risk of SPMs by considering the death as a competing event. Finally, we intuitively predicted the SPM probabilities of initial CC patients and identified the survivors at high risk of SPMs by constructing competingrisk nomograms.

Data Sources and Population Selection
We extracted the data from the SEER 18 registry database by using SEER * Stat 8.3.6 software (http://seer.cancer.gov/seerstat/). Up to now, the SEER database has collected and published cancer incidence and survival data covering ∼34.6% of the U.S. population. Cases of colon cancer were identified by "International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) Hist/behav, malignant." Patients aged 20-79 years, who were initially diagnosed as colon cancer with stage I-III between January 1998 and December 2011, and underwent colectomy were included in this study, ensuring long-term follow-up of at least 5 years to exist the risk of developing SPMs. The two key variables "sequence number" and "total number of in situ/malignant tumors for patient" of SEER database were used to determine the status of SPM. Cases that were diagnosed as synchronous cancers occurring SPM within 2 months after initial diagnosis, were subsequently excluded. In addition, all important covariates of these cases were complete without missing values. In the next step, we divided the involved CC patients into two groups: SPM cohort and the OOPM cohort. The flowchart of cases selection was shown in Supplementary Figure 1.

The Fine-Gray Proportional Subdistribution Hazards Modeling
The death of patients acted as a competing event of developing a second tumor and using Cox proportional hazards model would overestimate the incidence rate of the outcome with the passage of time (13). Thus, we used the Fine and Gray proportional subdistribution hazards model to evaluate the unbiased risks of developing a SPM, which could account for the competing event (14). Risk factors of total SPMs and top 5 SPMs for male and female CC survivors were analyzed, respectively. Candidate variables involved age at initial diagnosis, race, marital status, initial diagnosed site, tumor size, number of lymph nodes examined, histology, tumor grade, AJCC 6th stage, chemotherapy, and surgery. Multivariable competing risk models were conducted to find out the significant risk factors.

Competing-Risk Nomogram Construction and Evaluation
In order to help the clinicians to predict the individual SPM probability of male and female CC survivors, we established nomograms on the basis of the multivariate competing risk model. Next, we identified low-, medium-, and high-risk survivors by calculating the quantiles of total points and compared the difference of the SPM incidence among these subgroups. Validation of nomogram (15) was performed by calculating the concordance index (C-index) and plotting calibration curves by a bootstrapping method with 1,000 resamples. The C-index was used to quantify the discriminatory power of the model and the calibration plots were used to evaluate the accuracy of the nomogram. Furthermore, decision curve analysis (DCA) (16) which could calculate the net benefits at each risk threshold probability, was conducted to show the clinical effectiveness of the nomogram model. As far as we know, there was no nomogram with other model. Thus, we compared the nomograms with the models consisted of demographic characteristics (age, race, marital status) or tumor covariates (tumor size, tumor site, grade, stage, etc).

Statistical Analysis
All the data were statistically analyzed in R software (version 3.6.1, https://www.r-proje ct.org/). The Fine and Gray proportional subdistribution hazards model, competing-risk nomogram, C-index, calibration curves, Kaplan-Meier curves, cumulative incidence functions and DCA were conducted by using R 3.6.1 with relevant packages and functions, such as survival, cmprsk and stdca (https://www.mskcc.org/ departments/epidemiology-biostatistics/health-outcomes/ tutorial-r). A two-tailed value of P < 0.05 was considered statistically significant.

Patient Enrollment and Characteristics
A total of 56,930 survivors initially diagnosed with CC were included in this study; 5,013 (17.1%) of male patients and 3,592 (13.0%) of female patients developed SPMs occurring 2 months and more after the initial diagnosis. The follow-up time of over 50% patients was more than 10 years. Moreover, we found that prostate, lung and bronchus, urinary bladder and kidney, colon, and melanoma of the skin were the five most common sites of SPMs for male CC survivors, while breast, lung and bronchus, colon, uterus, urinary bladder and kidney were top 5 SPMs sites in female CC patients. The characteristics of CC survivors stratified by gender were exhibited in Tables 1, 2, respectively. Specifically, about 60% of patients in SPM cohort were aged 65-79 years and survivors with grade I-II accounted for approximately 80%. Married black male survivors and white female survivors were linked to the increased risk of a SPM. Moreover, right colon, or tumor size >5 cm, or number of lymph nodes examined <12, or stage I in all patients with CC showed the higher SPM incidence. Of these patients with SPMs, about 30 and 50% underwent chemotherapy and partial colectomy, respectively. The various causes of death in involved survivors were also displayed in Tables 1, 2. In total, 8,261 male CC patients (28.2%) and 6,720 female CC patients (24.31%) were dead, and the proportions of survivors with SPMs for causes of death, including first primary cancer, multiple malignancies and noncancer cause, were about 25, 45, and 30%, respectively.

Survival Analysis and Cumulative Incidence of a SPM
For male survivors, the median OS of the SPM cohort was 13.2 years, while the OOPM cohort did not reached the median survival time (Figure 1A). Subgroup analysis showed that the median OS of survivors with top 5 SPM was 18.2 years (prostate), 9.5 years (lung and bronchus), 14.3 years (urinary bladder and kidney), 11.8 years (colon), and 17.3 years (melanoma of the skin), respectively ( Figure 1B). Similarly, the SPM cohort, of which the median OS was 13.8 years, showed worse prognosis than the OOPM cohort ( Figure 1C). The median OS of female survivors with top 5 SPM was not reached (breast), 10.3 years (lung and bronchus), 13.5 years (colon), not reached (uterus), and 15.4 years (urinary bladder and kidney), respectively ( Figure 1D).

Unbiased Risk Factors of Developing a SPM
Risk predictors for developing a SPM after the initial CC diagnosis were estimated by using the Fine and Gray method, and the results of the characteristics were provided in Tables 3,  4. Older age, black race, married status, tumor size > 5 cm and number of lymph nodes examined <12 were significantly related to a higher risk of developing a SPM or a second primary prostate carcinoma in male survivors. For female survivors, older age, right colon, tumor size > 5 cm, tumor grade III-IV, stage I-II and chemotherapy were significantly linked to an increased risk of developing a SPM, while only three variables including age at initial diagnosis, race and initial diagnosed site showed significant difference in developing a second primary breast carcinoma, which might be not suitable for conducting the nomogram.

Competing-Risk Nomogram Construction and Validation
Competing-risk nomograms were established based on the previously mentioned factors to predict for developing a SPM in male survivors ( Figure 3A) or female survivors (Figure 4A), and for developing a second prostate carcinoma in male survivors ( Figure 5A). The risk scores of these variables were calculated in Supplementary Table 1. Low-, medium-, and high-risk survivors were identified using the 25th and 75th percentile values of the risk score. Compared with the low-risk group, the high-risk group exhibited a significantly higher cumulative incidence in 3-, 5-, and 10-year after the initial diagnosis (Supplementary Figures 2-4). The C-index of three competing-risk nomograms was 59.8, 56.8, and 63.7%, respectively, and the calibration curves revealed relatively excellent agreement between the nomogram prediction and the actual observation (Supplementary Figures 5-7). Furthermore, DCAs were performed on the competing-risk nomograms,   indicating that there were proper threshold probabilities for predicting a SPM in male or female survivors (Figures 3B,  4B), and for predicting a second primary prostate in male survivors ( Figure 5B) . Similarly, our model for predicting a second primary prostate carcinoma (C-index = 0.637) was more reliable than that of demographic characteristics (C-index = 0.628) and tumor covariates (C-index = 0.546). These results revealed that demographic characteristics played a key role in identifying SPM.

DISCUSSION
In fact, the number of cancer survivors in the U.S. is estimated to elevate to about 20 million by 2024 (5), and 17-19% of all new primary malignancies occurred in these survivors (17) of cancer. However, few studies focus on colon cancer survivors with SPMs, and most of these studies resulted in inaccurate estimates using logistic regression (10,18) or Cox regression model (19), in which the death is not considered as a competing event. Recently, Jia et al. studied the risk of second primary malignancies in patients with colorectal cancer and found that male or colon cancer survivors were prone to occurring SPMs, but the risk of the specific sites of SPMs was not involved (20). Thus, the current study aimed to identify the risk factors of the top 5 SPMs in male and female survivors with colon cancer, respectively. We ensured a long-term follow-up time after the initial diagnosis by screening patients from the latest population-based database between 1998 and 2011, subsequently, and to identify CC survivors with a SPM, regarding the death as a competing factor. Furthermore, nomograms were established to intuitively display the 3-, 5-, and 10-year prediction of SPM probabilities in male and female CC patients in this study, respectively. Some interesting findings were confirmed in the present study. Firstly, 17.1% of male survivors and 13.0% female survivors suffered from a SPM with a follow-up time of at least 5 years. Hence, it is significant to pay more attention to profile the characteristics of cancer survivors, as these traits might determine their health in future. Additionally, prostate and breast were the most common SPMs sites in male and female survivors, respectively, which is consistent with the estimated new cancer cases in 2020 (3). Ten-year cumulative incidence of the former was 5.32% in male while that of the latter was 3.23% in female. Further details of clinical and survival information about CC patients with SPMs were exhibited in this study. We also found that CC patients with only one primary malignancy experienced better prognosis than those with SPMs, regardless of gender. In addition, subgroup analysis of these with top 5 SPMs showed that lung and bronchus was the most fatal SPM site for both male and female survivors, with the consistence of most leading cancer type for deaths (3). Male patients with a second primary prostate carcinoma and female patients with a second primary breast carcinoma showed the best survival among top 5 SPMs sites. Therefore, it is necessary for CC survivors at high risk of SPMs to receive intensive and long-term surveillance, especially for a second primary prostate carcinoma in male patients and breast cancer in female survivors.
Secondly, identifying the comprehensive effects of demographic and tumor factors related to the risk of developing SPMs, attracts growing concern for CC survivor surveillance and management. As showed in our study, cumulative incidence of the death excessed that of SPM ∼8 years after the initial diagnosis in both male and female survivors, indicating that a large proportion of CC patients die before the development of a SPM and it is necessary to consider the death as a competing event. Hence, multivariable competing risk models were conducted to analyze the risk of SPMs in male or female survivors. Our multivariable competing risk models showed that male CC survivors with SPMs were prone to being older, black in race, married status, tumor size > 5 cm, number of lymph nodes examined <12, and stage I-II, while older age, right colon, bigger tumor size, tumor grade III-IV, stage I-II, and chemotherapy were significantly linked to a higher risk of developing a SPM  Age at initial diagnosis, years the potential role of marital status to the cancer risk, for that men with fewer sexual partner numbers were associated with a significantly decreased risk of prostate cancer (27) and married men may have more sexual activities. Additionally, tumor covariates (tumor size, tumor site, grade, stage, etc.) also were independent risk factor to determine the status of SPM, although their effects were relatively limited. It was reported that the location of colon cancer contributed to different incidence of second primary gastrointestinal malignancies, and the standardized incidence ratio of small intestinal cancer was higher in right colon cancer than that in left colon cancer (28). However, in our study, only female survivors with right colon cancer showed increased risk when compared to those with left colon cancer, and P-value is 0.048, showing the unstable statistical effect. The relationship between SPM risk and other tumor covariates (tumor size, stage, grade and number of lymph nodes examined) was not reported before. Our results revealed that the size of initial tumor was positively correlated with the FIGURE 3 | (A) Competing-risk nomogram for predicting the 3-, 5-, and 10-year risk of developing second primary malignancy (SPM) in male survivors. There are six factors in this nomogram, including age at initial diagnosis, race, marital status, number of lymph nodes examined (eLN) and stage; (B) AS shown, if the threshold probability was between 1 and 22%, then using the nomogram to predict the probability of developing SPM added more clinical benefits.

FIGURE 4 | (A)
Competing-risk nomogram for predicting the 3-, 5-, and 10-year risk of developing second primary malignancy (SPM) in female survivors. There are seven factors in this nomogram, including age at initial diagnosis, race, tumor site, tumor size, grade, stage and chemotherapy; (B) AS shown, if the threshold probability was between 1 and 17%, then using the nomogram to predict the probability of developing SPM added more clinical benefits.
incidence of SPMs, especially for developing a second colon cancer, which might be due to non-standard resection. Survivors with stage I-II usually experienced better prognosis and had enough follow-up time to develop more SPMs, so their risk was increasing. Nevertheless, there were some phenomena that are difficult to explain and these need to be further researched: (1) Female patients with grade III-IV were at higher risk; (2) Number of lymph nodes examined <12 in male survivors was an independent risk factor; (3) Chemotherapy could increase the SPM risk for female patients, mainly including a SPM site of lung and bronchus or urinary bladder and kidney.
Finally, regarding the sample size and the practicality of the models, we developed three competing-risk nomograms for predicting SPM risk of male or female survivors, and for predicting the probability of occurring a second primary prostate in male survivors. These nomograms could be effective for using common characteristics of CC patients to predict the 3-, 5-, and 10-year incidence probabilities of the outcome after the initial cancer diagnosis, considering the death as a competing factor. Moreover, the evaluation of our nomograms was demonstrated to have relatively high discrimination and calibration, and to reveal good clinical utility in the proper threshold probability range, which could help doctors identify CC survivors at the high risk to develop new primary cancers.
There are still some limitations in our study. First, this was a population-based retrospective analysis using the SEER database lacking some important risk factors for SPMs, such diet habit and lifestyle, family history of cancer, chemoradiotherapy protocols, and oncogene testing. It would be better to include the above variables in these three models, which might be the future direction of prediction for SPMs. Second, it is hard to distinguish the initial simultaneous cancers within a standard of 2-month interval or to identify metastases from SPMs, leading to the wrong estimates for the risk probabilities of developing SPMs. Of course, the diagnosis time of a SPM is also not the accurate time when it occurred, and with the development of rigorous surveillance and detection technology, these problems would be solved effectively. Finally, our models still need to be verified by external populations, although its internal validation showed good consistency. Risk factors for various SPMs sites of CC survivors need to be further studied to improve better surveillance strategies.

CONCLUSION
We profiled the characteristics of colon cancer survivors treated with colectomy and found that prostate cancer in male and breast cancer in female were the most common SPMs sites, respectively. Older age, black race in men and married male are the independent risk factors for developing SPMs. Subsequently, we established nomograms to predict the SPM probabilities and identify high-risk population. Therefore, it is suggested for these high-risk survivors that during postoperative follow-up of colon cancer, men can appropriately participate in prostate-specific antigen (PSA) examination, while women can appropriately participate in mammography examination.

DATA AVAILABILITY STATEMENT
Publicly available datasets were analyzed in this study. This data can be found here: https://seer.cancer.gov/.

ETHICS STATEMENT
No ethical approval was sought for this study, as the data used were collected from the public SEER database, which is available as open-access and anonymized data.

SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc. 2020.01154/full#supplementary-material Supplementary Figure 1 | The flowchart of cases selection.
Supplementary Figure 2 | The 3-, 5-, and 10-year cumulative incidence rates of SPMs among low-, medium-, and high-risk groups of male survivors. Risk stratification was conducted by the 25th and 75th percentile values of the risk score in the nomogram, which is 113 and 155, respectively. The cumulated incidence rates of these groups were assessed using the Fine-Gray method. Compared with the low-risk group (light-blue bar), the high-risk group (orange bar) exhibited a significantly higher cumulated incidence in 3-, 5-, and 10-year after the initial diagnosis.
Supplementary Figure 3 | The 3-, 5-, and 10-year cumulative incidence rates of SPMs among low-, medium-, and high-risk groups of female survivors. Risk stratification was conducted by the 25th and 75th percentile values of the risk score in the nomogram, which is 124 and 178, respectively. The cumulated incidence rates of these groups were assessed using the Fine-Gray method. Compared with the low-risk group (light-blue bar), the high-risk group (orange bar) exhibited a significantly higher cumulated incidence in 3-, 5-, and 10-year after the initial diagnosis.
Supplementary Figure 4 | The 3-, 5-, and 10-year cumulative incidence rates of second prostate carcinoma among low-, medium-, and high-risk groups of male survivors. Risk stratification was conducted by the 25th and 75th percentile values of the risk score in the nomogram, which is 126 and 159, respectively. The cumulated incidence rates of these groups were assessed using the Fine-Gray method. Compared with the low-risk group (light-blue bar), the high-risk group (orange bar) exhibited a significantly higher cumulated incidence in 3-, 5-, and 10-year after the initial diagnosis.