Edited by: Marco Invernizzi, University of Eastern Piedmont, Italy
Reviewed by: Nicola Fusco, University of Milan, Italy; Alexandra Resch, Medical University of Vienna, Austria; Marjan Rafat, Vanderbilt University, United States
This article was submitted to Women's Cancer, a section of the journal Frontiers in Oncology
†These authors have contributed equally to this work and share first authorship
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Breast cancer is worldwide the leading cancer among women (
Risk stratification by age and race have been extensively explored, demonstrating that survivors of premenopausal age at initial diagnosis and black women had an elevated risk of developing SPCs (
The purpose of the current research is to estimate cumulative incidence of SPCs and examine risk factors of developing SPCs in long-term early-stage breast cancer survivors in the presence of competing risks. Furthermore, we built an externally validated competing nomogram to help select patients at increased risk of developing SPCs.
Only Female breast cancer patients in the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) registry with histologically confirmed early-stage (stage I–III) who survived for 5 years and more were retrospectively reviewed from 1990 to 2010. In total, 250,764 eligible female patients at 20–80 years old with complete clinicopathological information were included. The inclusion and exclusion criteria was showed in flow chart (
Age was regrouped into four subpopulation (20–40, 41–60, 61–70, and 71–80). Race was regrouped into white race, black race and other race. Marital status was regrouped into married status, single status or divorced status. The hormone receptor (HR) status was stratified to HR positive (estrogen receptor (ER) or progesterone receptor (PR) was positive) and HR negative (both ER and PR were negative). Histology was divided as invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), mixed (mix of IDC and ILC), and other. Surgery was regrouped as breast conserving surgery (BCS) (including partial mastectomy, lumpectomy excisional biopsy, and segmental mastectomy) and mastectomy (including total mastectomy, modified radical mastectomy, radical mastectomy, extended radical mastectomy). Topography and morphology were used to explore the organ site specific risk using International Classification of Diseases for Oncology (ICD-O).
The cumulative incidence of SPCs was calculated based on the Gray method with a competing risk framework: deaths from IPBC or other causes, whichever occurred first, was regarded as competing event (
We randomly divided the entire cohort into a development cohort (75%) and another validation cohort (25%) for development and validation of the competing risks nomogram. Standardized mean differences (SMDs) was used to assess distributional differences in the baseline variables between the development and validation cohorts. Values of
The forward and backward stepwise methods was used to select the predictive variables from the development cohort for the prediction model based on the Akaike information criterion (AIC) (
We assessed the calibration for risks of developing SPCs by comparing the observed risks based on the Gray method with the mean predicted risks predicted risks from the prediction model. Likewise, an external validation was performed in the validation cohort. The C-index was also used to quantify the discrimination ability of the prediction model.
The decision curve analysis (DCA) in the validation cohort was used to examine the clinical utility and net benefits of competing risks model for developing SPCs. DCA is a suitable method for evaluating alternative diagnostic and prognostic strategies that has advantages over other commonly used measures and techniques (
All statistical analysis were conducted using R software (
250,764 early-stage IPBC patients who survived >5 years between 1990 and 2010 were included in the entire cohort. Of those patients, 30,285 (12.08%) patients developed SPCs. Twenty thousand one hundred and seventy (8.04%) patients died from IPBC, and 26,572 (10.60%) died from other causes. Second breast cancers represented 13,105 (43.27%) of all SPCs followed by gastrointestinal (GI) at 4,325 (14.28%), lung at 3,203 (10.58%), female genital tract at 2,923 (9.65%), skin at 1,467 (4.84%), central nervous system at 1,333 (4.40%), leukemias at 1,253 (4.14%), urinary tract at 1,192 (3.94%), and lymphoma 546 at (1.80%). The median latency from diagnosis of IPBC to subsequent diagnosis of SPCs was 116 months (25–75% interquartile range, 86–153 months). The detailed information of population is summarized in
Patient characteristics and clinicopathological variables with stratified events.
20–40 | 23,537 | 18,316 (10.54%) | 2,646 (7.47%) | 314 (1.18%) | 2,261 (7.47%) |
41–60 | 131,791 | 102,951 (59.26%) | 9,996 (48.09%) | 4,280 (16.11%) | 14,564 (48.09%) |
61–70 | 56,494 | 35,866 (20.64%) | 4,288 (27.89%) | 7,894 (29.71%) | 8,446 (27.89%) |
71–80 | 38,942 | 16,604 (9.56%) | 3,240 (16.56%) | 14,084 (53%) | 5,014 (16.56%) |
White | 207,149 | 142,231 (81.87%) | 16,455 (83.73%) | 23,106 (86.96%) | 25,357 (83.73%) |
Black | 22,030 | 15,262 (8.78%) | 2,114 (8.52%) | 2,074 (7.81%) | 2,580 (8.52%) |
Other | 21,585 | 16,244 (9.35%) | 1,601 (7.75%) | 1,392 (5.24%) | 2,348 (7.75%) |
Married | 160,206 | 115,200 (66.31%) | 12,298 (63.9%) | 13,355 (50.26%) | 19,353 (63.9%) |
Single | 32,416 | 23,617 (13.59%) | 2,808 (11.51%) | 2,506 (9.43%) | 3,485 (11.51%) |
Divorced | 58,142 | 34,920 (20.1%) | 5,064 (24.59%) | 10,711 (40.31%) | 7,447 (24.59%) |
Right | 126,809 | 87,974 (50.64%) | 10,261 (50.06%) | 13,413 (50.48%) | 15,161 (50.06%) |
Left | 123,955 | 85,763 (49.36%) | 9,909 (49.94%) | 13,159 (49.52%) | 15,124 (49.94%) |
Central portion | 14,614 | 9,642 (5.55%) | 1,376 (5.8%) | 1,839 (6.92%) | 1,757 (5.8%) |
Upper-inner quadrant | 26,492 | 18,529 (10.66%) | 2,043 (10.86%) | 2,632 (9.91%) | 3,288 (10.86%) |
Lower-inner quadrant | 13,472 | 9,006 (5.18%) | 1,142 (5.73%) | 1,590 (5.98%) | 1,734 (5.73%) |
Upper-outer quadrant | 93,876 | 65,550 (37.73%) | 6,828 (38.26%) | 9,912 (37.3%) | 11,586 (38.26%) |
Lower-outer quadrant | 17,581 | 12,300 (7.08%) | 1,409 (6.91%) | 1,780 (6.7%) | 2,092 (6.91%) |
Other | 84,729 | 58,710 (33.79%) | 7,372 (32.45%) | 8,819 (33.19%) | 9,828 (32.45%) |
IDC | 196,061 | 136,173 (78.38%) | 15,604 (78.1%) | 20,631 (77.64%) | 23,653 (78.1%) |
ILC | 16,219 | 11,295 (6.5%) | 1,575 (5.52%) | 1,676 (6.31%) | 1,673 (5.52%) |
Mixed | 19,768 | 13,817 (7.95%) | 1,769 (7.88%) | 1,796 (6.76%) | 2,386 (7.88%) |
Other | 18,716 | 12,452 (7.17%) | 1,222 (8.5%) | 2,469 (9.29%) | 2,573 (8.5%) |
Well | 44,593 | 30,982 (17.83%) | 1,683 (19.78%) | 5,937 (22.34%) | 5,991 (19.78%) |
Moderate | 107,443 | 73,030 (42.03%) | 9,082 (43.33%) | 12,209 (45.95%) | 13,122 (43.33%) |
Poor | 93,890 | 66,675 (38.38%) | 8,913 (34.41%) | 7,880 (29.66%) | 10,422 (34.41%) |
Undifferentiated | 4,838 | 3,050 (1.76%) | 492 (2.48%) | 546 (2.05%) | 750 (2.48%) |
I | 87,312 | 54,392 (31.31%) | 4,165 (48.54%) | 14,054 (52.89%) | 14,701 (48.54%) |
II | 126,028 | 94,712 (54.51%) | 9,152 (40.71%) | 9,834 (37.01%) | 12,330 (40.71%) |
III | 37,424 | 24,633 (14.18%) | 6,853 (10.74%) | 2,684 (10.1%) | 3,254 (10.74%) |
BCS | 135,904 | 95,767 (55.12%) | 8,114 (40.23%) | 13,354 (50.26%) | 18,669 (61.64%) |
Mastectomy | 114,860 | 77,970 (44.88%) | 12,056 (59.77%) | 13,218 (49.74%) | 11,616 (38.36%) |
Negative | 49,400 | 36,315 (20.9%) | 3,128 (19.76%) | 3,972 (14.95%) | 5,985 (19.76%) |
Positive | 201,364 | 137,422 (79.1%) | 17,042 (80.24%) | 22,600 (85.05%) | 24,300 (80.24%) |
With | 120,333 | 74,077 (42.64%) | 7,901 (57.73%) | 20,871 (78.55%) | 17,484 (57.73%) |
Without | 130,431 | 99,660 (57.36%) | 12,269 (42.27%) | 5,701 (21.45%) | 12,801 (42.27%) |
With | 113,100 | 76,559 (44.07%) | 9,703 (41.6%) | 14,238 (53.58%) | 12,600 (41.6%) |
Without | 137,664 | 97,178 (55.93%) | 10,467 (58.4%) | 12,334 (46.42%) | 17,685 (58.4%) |
We randomly divided entire cohort into two parts: a development cohort (188,073 patients) and a validation cohort (62,691 patients). Baseline characteristics, such as initial diagnosis age, race and treatment-related factor, were similarly distributed in the development and validation cohorts (
The pre-specified variable selection process selected eight variables for inclusion in the multivariable Fine and Gray model: age at initial diagnosis, race, laterality, histology, stage, HR, chemotherapy, and radiotherapy. Except laterality, all variables were included in the final model. Compared to a reference age group of 20–40 years, survivors of an elderly age had substantially elevated risks of SPCs [subdistribution hazard ratio (SHR) of 1.206 (95% CI: 1.100–1.323;
Factors associated with development of second primary cancer risks.
20–40 | ref | ||
41–60 | 1.206 | 1.100–1.323 | <0.001 |
61–70 | 1.648 | 1.494–1.818 | <0.001 |
71–80 | 1.332 | 1.197–1.482 | <0.001 |
White | ref | ||
Black | 1.101 | 1.015–1.194 | 0.021 |
Other | 0.993 | 0.914–1.079 | 0.860 |
IDC | ref | ||
ILC | 0.974 | 0.881–1.077 | 0.600 |
Mix | 1.092 | 1.004–1.188 | 0.039 |
Other | 0.942 | 0.867–1.024 | 0.160 |
I | ref | ||
II | 0.945 | 0.896–0.996 | 0.034 |
III | 0.814 | 0.750–0.884 | <0.001 |
Negative | ref | ||
Positive | 0.880 | 0.829–0.933 | <0.001 |
With | ref | ||
Without | 0.88 | 0.832–0.931 | <0.001 |
With | ref | ||
Without | 1.161 | 1.109–1.217 | <0.001 |
Furthermore, the effects of initial cancer-treatment (chemotherapy and radiotherapy) and HR status on the SPCs risk in selected organ sites were estimated based on the multivariable Fine and Gray risk model. We found that, after adjusting for age, race, histology, IPBC stage, HR, and chemotherapy, patients with radiotherapy had an elevated risk of any SPCs and with increased risks of lung cancer (SHR = 1.109; 95% CI: 1.033–1.192;
The forest plot comparing radiotherapy-related risk by selected organ sites. Head and neck: ICD-O codes C00-C14. Esophagus: ICD-O codes C15. Lung and trachea: ICD-O codes C33-C34. Breast: ICD-O codes C50. Uterus: ICD-O codes C54-C55. Ovary: ICD-O codes C56-C57. Urinary tract: ICD-O codes C63-C68. GI: Gastrointestinal, ICD-O codes C16-C26. AML: acute myeloid leukemia, ICD-O morphology codes 9860-9911. Other leukemia: ICD-O morphology codes 9912-9989. Lymphoma: ICD-O morphology codes: 9590-9837. SHR: Subdistribution hazard ratio. 95% CI: confidence interval.
The forest plot comparing chemotherapy-related risk by selected organ sites. Head and neck: ICD-O codes C00-C14. Esophagus: ICD-O codes C15. Lung and trachea: ICD-O codes C33-C34. Breast: ICD-O codes C50. Uterus: ICD-O codes C54-C55. Ovary: ICD-O codes C56-C57. Urinary tract: ICD-O codes C63-C68. GI: Gastrointestinal, ICD-O codes C16-C26. AML: acute myeloid leukemia, ICD-O morphology codes 9860-9911. Other leukemia: ICD-O morphology codes 9912-9989. Lymphoma: ICD-O morphology codes: 9590-9837. SHR: subdistribution hazard ratio; 95% CI: confidence interval.
The forest plot comparing effect of HR status on second primary cancer risks by selected organ sites. Head and neck: ICD-O codes C00-C14. Esophagus: ICD-O codes C15. Lung and trachea: ICD-O codes C33-C34. Breast: ICD-O codes C50. Uterus: ICD-O codes C54-C55. Ovary: ICD-O codes C56-C57. Urinary tract: ICD-O codes C63-C68. GI: Gastrointestinal, ICD-O codes C16-C26. AML: acute myeloid leukemia, ICD-O morphology codes 9860-9911. Other leukemia: ICD-O morphology codes 9912-9989. Lymphoma: ICD-O morphology codes: 9590-9837. SHR: Subdistribution hazard ratio; 95% CI: confidence interval.
Factors associated with development of second primary cancer risks by organ sites within the entire cohort.
20–40 | Ref | Ref | Ref | Ref | Ref | Ref |
41–60 | 1.121 (1.073–1.172) | 1.525 (1.053–2.21) | 4.808 (3.583–6.451) | 1.593 (0.675–3.76) | 0.754 (0.714–0.797) | 3.48 (2.6–4.659) |
61–70 | 1.475 (1.406–1.547) | 1.747 (1.175–2.598) | 10.05 (7.475–13.51) | 2.296 (0.934–5.65) | 0.662 (0.621–0.706) | 4.391 (3.256–5.92) |
71–80 | 1.200 (1.139–1.264) | 1.681 (1.103–2.562) | 7.183 (5.310–9.715) | 2.651 (1.037–6.78) | 0.434 (0.402–0.468) | 3.574 (2.618–4.88) |
White | Ref | Ref | Ref | Ref | Ref | Ref |
Black | 1.117 (1.072–1.164) | 0.550 (0.36–0.841) | 0.990 (0.866–1.133) | 0.904 (0.453–1.8) | 1.366 (1.291–1.446) | 1.103 (0.931–1.306) |
Other | 0.950 (0.910–0.990) | 1.106 (0.821–1.49) | 0.649 (0.555–0.759) | 0.782 (0.379–1.62) | 1.079 (1.015–1.146) | 1.111 (0.944–1.307) |
IDC | Ref | Ref | Ref | Ref | Ref | Ref |
ILC | 0.983 (0.935–1.034) | 1.072 (0.749–1.536) | 0.937 (0.807–1.088) | 1.276 (0.664–2.45) | 1.009 (0.931–1.093) | 0.802 (0.646–0.996) |
Mix | 1.065 (1.021–1.111) | 0.939 (0.672–1.311) | 0.902 (0.786–1.034) | 0.717 (0.333–1.54) | 1.217 (1.143–1.295) | 0.944 (0.791–1.127) |
Other | 1.024 (0.983–1.067) | 0.655 (0.446–0.962) | 1.100 (0.974–1.242) | 0.807 (0.408–1.6) | 1.045 (0.983–1.112) | 0.996 (0.84–1.181) |
I | Ref | Ref | Ref | Ref | Ref | Ref |
II | 0.939 (0.915–0.964) | 0.970 (0.786–1.196) | 0.991 (0.913–1.076) | 1.169 (0.761–1.8) | 0.881 (0.846–0.917) | 1.007 (0.904–1.122) |
III | 0.802 (0.769–0.836) | 0.943 (0.692–1.284) | 0.930 (0.819–1.057) | 1.428 (0.772–2.64) | 0.651 (0.61–0.695) | 0.898 (0.761–1.06) |
Negative | Ref | Ref | Ref | Ref | Ref | Ref |
Positive | 0.912 (0.886–0.939) | 0.876 (0.698–1.100) | 0.967 (0.879–1.064) | 0.763 (0.493–1.18) | 0.842 (0.807–0.879) | 1.009 (0.893–1.141) |
Without | Ref | Ref | Ref | Ref | Ref | Ref |
With | 1.193 (1.165–1.221) | 1.053 (0.882–1.258) | 1.109 (1.033–1.192) | 1.017 (0.71–1.46) | 1.389 (1.339–1.439) | 0.993 (0.903–1.092) |
Without | Ref | Ref | Ref | Ref | Ref | Ref |
With | 0.931 (0.905–0.957) | 1.162 (0.927–1.455) | 0.895 (0.818–0.979) | 0.783 (0.489–1.260) | 0.891 (0.854–0.93) | 1.02 (0.913–1.141) |
20–40 | Ref | Ref | Ref | Ref | Ref | Ref |
41–60 | 0.912 (0.718–1.158) | 3.436 (2.234–5.283) | 2.325 (1.900–2.840) | 1.356 (0.791–2.330) | 2.657 (1.865–3.784) | 2.795 (1.517–5.15) |
61–70 | 1.041 (0.798–1.358) | 6.714 (4.338–10.39) | 4.840 (3.943–5.940) | 2.522 (1.445–4.400) | 4.928 (3.436–7.066) | 7.167 (3.877–13.25) |
71–80 | 0.931 (0.694–1.249) | 5.507 (3.517–8.622) | 5.579 (4.528–6.880) | 2.763 (1.501–5.090) | 5.146 (3.562–7.436) | 9.389 (5.022–17.56) |
White | Ref | Ref | Ref | Ref | Ref | Ref |
Black | 0.499 (0.357–0.696) | 0.965 (0.766–1.216) | 1.206 (1.071–1.360) | 1.032 (0.661–1.610) | 0.895 (0.719–1.114) | 1.004 (0.713–1.41) |
Other | 0.791 (0.601–1.041) | 0.552 (0.416–0.732) | 1.319 (1.182–1.470) | 1.306 (0.878–1.940) | 0.715 (0.567–0.901) | 0.8 (0.551–1.16) |
IDC | Ref | Ref | Ref | Ref | Ref | Ref |
ILC | 1.004 (0.726–1.388) | 1.002 (0.788–1.274) | 0.937 (0.816–1.080) | 0.577 (0.306–1.090) | 0.932 (0.74–1.173) | 0.858 (0.583–1.26) |
Mix | 0.796 (0.582–1.088) | 0.934 (0.748–1.166) | 0.942 (0.831–1.070) | 0.809 (0.490–1.330) | 1.015 (0.833–1.236) | 1.018 (0.73–1.42) |
Other | 0.864 (0.662–1.127) | 0.822 (0.652–1.037) | 0.980 (0.871–1.100) | 1.138 (0.753–1.720) | 0.938 (0.768–1.146) | 1.101 (0.803–1.51) |
I | Ref | Ref | Ref | Ref | Ref | Ref |
II | 0.968 (0.823–1.14) | 1.011 (0.881–1.16) | 1.016 (0.942–1.090) | 0.93 (0.684–1.260) | 0.903 (0.798–1.023) | 0.953 (0.775–1.17) |
III | 0.746 (0.575–0.967) | 0.875 (0.702–1.09) | 1.015 (0.904–1.140) | 1.629 (1.101–2.410) | 0.744 (0.606–0.913) | 1.317 (0.998–1.74) |
Negative | Ref | Ref | Ref | Ref | Ref | Ref |
Positive | 0.483 (0.415–0.563) | 1.214 (1.02–1.444) | 0.973 (0.891–1.060) | 0.842 (0.624–1.140) | 1.12 (0.961–1.304) | 0.961 (0.761–1.22) |
Without | Ref | Ref | Ref | Ref | Ref | Ref |
With | 1.095 (0.947–1.266) | 1.003 (0.891–1.13) | 0.938 (0.879–1.000) | 1.298 (1.005–1.670) | 1.116 (1–1.245) | 1.169 (0.973–1.4) |
Without | Ref | Ref | Ref | Ref | Ref | Ref |
With | 1.112 (0.938–1.319) | 0.911 (0.782–1.062) | 0.926 (0.852–1.010) | 1.068 (0.777–1.470) | 0.951 (0.829–1.09) | 1.408 (1.129–1.76) |
The established nomogram based on the multivariable Fine and Gray model shows the relative importance of each independent variable: age was the vital predictors of developing SPCs, followed by the IPBC stage, radiotherapy, race, HR status, histology, and chemotherapy (
Competing risks nomogram for predicting the 10-, 15-, and 20-year risk of developing second primary cancers. The competing risks nomogram provides a method to calculate 10-, 15-, and 10-year probability of cumulative incidence (CI) of developing second primary cancers (SPCs) on the basis of a patient's combination of covariates. To use, locate the patient's age at initial diagnosis, draw a line straight up to the points axis to establish the score associated with that age. Repeat for the other five covariates (race, histology, stage, HR, chemotherapy, and radiotherapy). Add the score of each covariate together and locate the total score on the total points axis. Draw a line straight down to the 10-, 15-, and 20-year SPCs cumulative incidence axis to obtain the individual probability.
Cumulative incidence of developing SPCs across different risk subgroups defined nomogram-predicted risk score, which shows a wide stratification of the SPC risks at 15 years, from 12.01% for the 25th interquartile group to 17.42% for the 75th interquartile group with a statistical significance according to the Gray test (
Decision curve analysis for the competing risks nomogram for 15-year second primary cancer risks in the validation cohort. The X-axis is the risk threshold probability that changes from 0 to 1 (right truncated at 0.25) and the Y-axis is the calculated net benefit for a given threshold probability. The dashed lines depict the net clinical benefit of the competing risks–based selection strategy for intervention, whereas the gray and black curves display the net benefits in the alternative strategies of treating all patients (gray) vs. treating no patients (black) in the cohort.
In the present study, we calculate the cumulative incidence of SPCs among survivors of early-staged IPBC in the presence of competing events, evaluate risk factors for developing SPCs based on the multivariate Fine and Gray model, and build and externally validate a clinical prediction model. Our study supports and expands on previous studies demonstrating an elevated standardized incidence ratio (SIR) for SPCs following an IPBC, especially among elderly, early-stage, HR-negative, and irradiated survivors compared with the general population. To our knowledge, this is the first available nomogram for developing SPCs in IPBC survivors in the presence of competing events, which was helpful in individual risk estimation, patient follow-up and counseling. The DCA inform clinical decisions was better than the strategies of treat all or treat none across a wide range of thresholds between 0.01 and 0.24, which shows the higher clinical utility of our risk prediction model.
The previous studies demonstrated that young patients had a higher SIR than elderly patients (
Few studies have explored the effect of the extent of the initial disease on the development of SPCs. We found that increased patients with higher IPBC stage had a declined risk of SPCs, necessarily attributed to higher possibility of mortality from IPBC before SPCs occur (
In the present study, we compared treatment-related SPC risks by selected organ sites. A study estimated that 9% of any SPCs and 25% of the irradiation-associated site SPCs were ascribed to radiation therapy (
A previous study also identified that black breast cancer survivors had a higher risk of developing SPCs (
Cumulative incidence of developing SPCs elevated over time and did not plateau. There is a significant difference in OS between survivors with and without SPCs. Consistent with previous studies, our study found that HR negative with radiotherapy and black race were significantly associated with increased risks of SPCs. In contrast, chemotherapy was associated with a modest protective effect. Inconsistent with previous reports, we found that elderly patients was associated with an elevated risk of developing SPCs. For the first time, we found that lower IPBC stage was also associated with elevated risk of developing SPCs. Furthermore, an externally validated clinical prediction model was established to help select high-risk patients.
The datasets generated for this study are available on request to the corresponding author.
DL conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents, materials and analysis tools, prepared figures and/or tables, and authored or reviewed drafts of the paper. SW and XT conceived and designed the experiments, performed the experiments, analyzed the data. CZ, NZ, YC, and DX performed the experiments and authored or reviewed drafts of the paper. YY conceived and designed the experiments, performed the experiments, authored or reviewed drafts of the paper, and approved the final draft.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at:
The flow chart of the detailed inclusion and exclusion criteria.
Internal (
Cumulative incidence of second primary cancers (SPCs) by different risk subgroups defined by the estimated nomogram-predicted risk score. The marginal cumulative incidence of SPCs was calculated, and the difference of the cumulative incidences across distinct risk subgroups was tested using the Gray method.
Comparisons of patient characteristics of the study population in the development and validation cohorts.
Point assignment and risk score in the nomogram.