378 Original Article Page 1 of 14 Developing and validating a novel nomogram used a competing-risks model for predicting the prognosis of primary fallopian tube carcinoma: a retrospective study based on the SEER database Chengzhuo Li1,2#, Junyuan Li3#, Qiao Huang4, Xiaojie Feng1,2, Fanfan Zhao1,2, Fengshuo Xu1,2, Didi Han1,2, Jun Lyu1,2 1Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China; 2School of Public Health, Xi'an Jiaotong University Health Science Center, Xi’an, China; 3Medical Centre of Stomatology, The First Affiliated Hospital of Jinan University, Guangzhou, China; 4Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China Contributions: (I) Conception and design: C Li, J Lyu; (II) Administrative support: J Lyu; (III) Provision of study materials or patients: J Li, F Xu; (IV) Collection and assembly of data: J Li, X Feng, F Zhao; (V) Data analysis and interpretation: C Li, Q Huang, D Han; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. #These authors contributed equally to this work. Correspondence to: Jun Lyu. Department of Clinical Research, The First Affiliated Hospital of Jinan University, 613 West Huangpu Avenue, Tianhe District, Guangzhou 510630, China. Email: [email protected]. Background: The current prognostic methods for primary fallopian tube carcinoma (PFTC) are inadequate. This study is the first to use a competing-risks model to perform an accurate analysis of the prognostic factors for PFTC cause-specific death (CSD). We used the model to established a nomogram for the 3-, 5-, and 8-year CSD rates based on the identified prognostic factors. Methods: This study selected 1,924 patients from the SEER (Surveillance, Epidemiology, and End Results) database. The cumulative incidence function (CIF) was used in univariate analyses, and Gray’s test was used to determine the intergroup difference in the CIF. We then used the subdistribution proportional hazards model in a multivariate analysis. We finally used the prognostic factors identified in the analysis of the competing-risks model to construct a 3-, 5-, and 8-year CSD nomogram for PFTC patients. The concordance index (C-index) and calibration plots were used to evaluate the discrimination ability and consistency of the model. Results: The subdistribution proportional hazards model showed that age, histological type, FIGO stage, and the log of the ratio between the numbers of positive and negative lymph nodes (LODDS) were independent prognostic factors for CSD. The 3-, 5-, and 8-year C-indexes were 0.744, 0.744, and 0.733 in the training cohort, and 0.737, 0.748, and 0.721 in the validation cohort. In the calibration plots, the forecast lines were very close to the reference lines. Conclusions: This study is the first to analyze the prognostic factors for PFTC based on a competing- risks model. This model indicates that age, histological type, FIGO stage, and LODDS are significant prognostic factors affecting CSD in PFTC patients. We have also constructed the first 3-, 5-, and 8-year CSD nomogram for PFTC patients. This nomogram exhibits good discrimination ability and accuracy and can help clinicians to provide individualized prognostic analysis for PFTC patients. Keywords: Primary fallopian tube carcinoma (PFTC); SEER; competing risk model; nomogram; cancer-specific death Submitted Jul 19, 2020. Accepted for publication Dec 16, 2020. doi: 10.21037/atm-20-5398 View this article at: http://dx.doi.org/10.21037/atm-20-5398 © Annals of Translational Medicine. All rights reserved. Ann Transl Med 2021;9(5):378 | http://dx.doi.org/10.21037/atm-20-5398 Page 2 of 14 Li et al. A competing-risks nomogram for primary fallopian tube carcinoma Introduction Research shows that the Cox model is not suitable for identifying the risk factors in the presence of competing Primary fallopian tube carcinoma (PFTC) is a rare risks. Fine and Gray (10) proposed a subdistribution gynecological tumor that accounts for 0.14–1.8% of genital proportional hazards model, which has been widely applied malignancies (1). The incidence of fallopian tube carcinoma (11-13). The subdistribution proportional hazards model is increasing, with the rate in North America reportedly can directly perform regression modeling on competitive increasing from 0.22 per 1 million females in 1999–2001 to risk data and then obtain more accurate prognostic factors 0.62 per 1 million females in 2011–2012 (2), and another related to specific outcomes (14). For clinical decision- study finding that the diagnosis rate increased fourfold from making in the real world where competing risks do exist, 2001 to 2014 (3). Additionally, recent studies have shown actual rather than virtual risks are usually more important. that many tumors classified as high-grade serous carcinomas The cumulative incidence provides an estimate of the of the ovary or peritoneum might originate in the fallopian percentage of patients who actually maintain the event, and tube (4,5). This situation means that the incidence of PFTC the subdistribution proportional hazards model provides might be underestimated, and hence that more attention actual risk factors. Therefore, the competitive risk model should be paid to PFTC. is more meaningful for individual patient prognosis The difficulty of diagnosing PFTC early often results consultation and clinical resource utilization (15,16). in a poor prognosis. A retrospective analysis found that Nomograms are widely used as prognostic devices in the 5-, 8-, and 15-year overall survival rates were 44.7%, oncology and medicine since they allow individualized 23.8%, and 18.8%, respectively, while the disease-free predictions and both doctors and patients find their survival rates were 27.3%, 17%, and 14% (6). Diagnosing visualizations easy to understand (17). We are not aware PFTC preoperatively is extremely difficult, whereas surgical of any previous research that has constructed a PFTC findings enable doctors to determine a precise histological prognostic nomogram, and so another purpose of this diagnosis, staging, and prognosis (1). and so all of the research was using the prognostic factors derived from subjects selected for inclusion in our study had undergone the competing-risks model to construct and validate the surgery. 3-, 5-, and 8-year cause-specific death (CSD) nomogram Competing risks are common in the medical arena, for PFTC patients, which can be used to guide clinical and the standard Cox model leads to incorrect and decisions. We present the following article in accordance biased results because it does not account for competing with the TRIPOD reporting checklist (available at http:// events (7). Competing-risks models divide the outcome dx.doi.org/10.21037/atm-20-5398). into three categories: censored events, the specific event, and competing-risks events (8). Competitive events are Methods events that may affect the probability of an observed event or hinder its occurrence. When researchers pay attention The study was conducted in accordance with the to the death of specific cancer, patients may die from other Declaration of Helsinki (as revised in 2013). Because the cancers, suicide, traffic accidents, etc. The traditional information in the SEER database does not require the Cox regression classifies these patients as censored data, patient’s explicit consent, the study is waived from ethical which incorrectly estimates the cumulative incidence and approval. The informed patient consent is not required due HR value of the target outcome, and then deriving biased to the retrospective nature of the study. prognostic factors (7). Competitive risk becomes particularly important when analyzing the elderly population or long- Patient selection term prognosis (9). The purpose of the present study was to utilize the large sample available in the Surveillance, This study analyzed data obtained from the SEER database. Epidemiology, and End Results (SEER) database to identify The SEER Program collects and publishes cancer incidence the long-term prognostic factors for PFTC. It means that and survival data from population-based cancer registries there may be a lot of competition events in the research. covering approximately 34% of the US population. If Cox regression is directly used for analysis, bias will be This large database provides relatively accurate clinical generated. Therefore, we adopted a competitive risk model information (18). We search the database from SEER 18 suitable for this type of data and research objectives. Regs Custom Data (with additional treatment fields), Nov © Annals of Translational Medicine. All rights reserved. Ann Transl Med 2021;9(5):378 | http://dx.doi.org/10.21037/atm-20-5398 Annals of Translational Medicine, Vol 9, No 5 March 2021 Page 3 of 14 SEER database Inclusion criteria: - Primary sites: “C57.0-fallopian tube” - All the ICD-O-3 hist/behave of the PFTC - Data from 1975 to 2016 PFTC patients under the above criteria (n=3,636) Exclusion criteria: - Race unknown (n=19) - Laterality unknown (n=55) - Patients without confirmed positive histological diagnosis (n=16) - The number of positive lymph nodes unknown (n=1,446) - The number of examined lymph nodes unknown (n=90) - Lymph nodes unknown (n=77) - Without surgery (n=1) - Survival time unknown (n=8) Included primary cohort (n=1,924) Training cohort to Validation cohort to verify the construct the nomogram nomogram (n=1,346, 70%) (n=578, 30%) Figure 1 Data selection flowchart. 2018 Sub (1975–2016 varying), including for chemotherapy as log(pnod + 0.5)/(tnod – pnod + 0.5), where 0.5 is added data. All of the data were downloaded using SEER software to the denominator to avoid an infinite number and thus (version 8.3.6). Because some of the SEER research data also to the numerator to reduce bias (19). is publicly available, no informed consent or institutional The age at diagnosis and the year of diagnosis were review board approval was required.