Epidemiological and survival outcomes of neuroendocrine carcinoma of the breast: a SEER data analysis

Introduction

Neuroendocrine carcinoma of the breast (NECB) was initially discovered and reported by Feyrter and Hartmann in 1963, and is a special type of breast cancer that represents a rare subtype (1,2). NECB reportedly ranges from 0.1% to 5% of breast cancer cases (3-5). According to the 2003 World Health Organization (WHO) classification (6), breast carcinomas with neuroendocrine features are classified into three groups based on morphology: (I) solid neuroendocrine carcinoma, (II) small-cell carcinoma/oat cell carcinoma, and (III) large-cell neuroendocrine carcinoma. The reported proportions of these groups have varied widely, and hence we have reason to insist that the prevalence and distribution of NECB still remain to be further studied and clarified. In this context, the real epidemiological, clinical, and prognostic features of NECB still remain to be clarified.

The Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute was established in 1973 and has been a valued source of high-quality information on the incidence and survival of cancer in the United States, covering 48% of its population (based on the latest SEER*Explorer software). SEER data have been used in various studies to explore cancer incidence and survival for etiological and outcome research related to cancer. Data on approximately 450,000 cases of malignant and in situ cancers are collected each year (7), and the SEER database now contains large amounts of data on NECB during 2000–2017. Our objective was to analyze SEER data to determine the epidemiology and survival prognosis of NECB. We present this article in accordance with the STROBE reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-368/rc).

Methods

Patient selection

All cases in this study were obtained from SEER database and using SEER*Stat software (www.seer.cancer.gov) which was released in April 2022 (version 8.4.0: “SEER Research Plus Data, 18 Registers, Nov. 2019 Sub 2000–2017”). The approval and informed consent of the Ethics Committee were not required for the data to be analyzed. We collected information on age, sex, race, marital status, pathological type, registration location, the use of therapeutic modalities including surgery, radiation, and chemotherapy, American Joint Committee on Cancer (AJCC) stage, breast subtype and outcomes (survival/death). The SEER database mainly includes variables that comprise patient demographics, primary tumor location, morphology, and topographic map codes from the International Classification of Tumor Diseases, Third Edition (ICD-O-3). We selected NECB cases diagnosed during 2000–2017. The study only included the breast site in Site Recode ICD-O-3/WHO 2008. Patients fitting any of the following criteria were also excluded: unknown survival time; outcomes of dead, missing, or unknown; or unknown race. The study finally included 7,856 eligible patients diagnosed with NECB.

Study variables

Definitions and information about the variables of age, sex, race, marital status, pathological type, registration location, and survival time can be found in the SEER database. Cancer-specific survival (CSS) was the primary study endpoint. Dying from NECB was considered as an event, but the survival statuses of the patients were censored. We divided all patients into two groups based on the age at diagnosis: <60 and ≥60 years. For marital status, patients were divided into married, divorced/separated, widowed, unmarried, and others groups. Unmarried patients included single patients and those with a domestic partner. For race, patients were divided into white, black, and others. The ICD-O-3 “Histology Code and Behavior” malignancy list (“his” variable) was used to distinguish between the pathological types of solid neuroendocrine, small cell/oat cell, and large cell neuroendocrine carcinomas, our study focused on non-invasive neuroendocrine tumors, and we classified solid neuroendocrine carcinomas as neoplastic tumors while large cell neuroendocrine carcinomas and cell/oat cell carcinomas were classified as non-neoplastic tumors. For registration location, patients were diagnosed in 1 of 13 states of the United States. For surgery of primary tumor, surgery combined with radiation, no cancer cause surgery (surgeries performed are not aimed at addressing or treating the cancer), radiation, and chemotherapy, the patients were all divided into two groups: yes and no/unknown. For AJCC stage were classified into four groups. Breast subtype were divided into four groups according to the expressions of hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2).

Statistical analysis

CSS was defined as the time from diagnosis to dying of NECB. The Kaplan-Meier method was used to evaluate CSS in different groups. Logarithmic rank test was applied to analyze the differences between curves. Univariate and multivariate Cox proportional hazard models were used to evaluate hazard ratios and 95% confidence intervals to determine the association between NECB patient survival and multiple predictors, with statistical significance defined as P<0.05. All data were analyzed using SPSS statistical software (version 24.0, IBM, New York, NY, USA).

Ethics statement

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The SEER Program has a strict policy to protect patient privacy, and all data were de-identified prior to analysis. No informed consent was required for this retrospective study.

Results

Population analysis

During 2000–2017, 1,143,556 mammary neoplasm cases were recorded in the SEER database, 12,263 cases of which were NECB, indicating that NECB accounted for 1.07% of all mammary neoplasms. We excluded 4,352 patients due to unknown follow-up data; At the same time, we compared the basic characteristics of included and excluded patients, and found that there was no significant difference in their basic characteristics. Finally, 7,856 patients were included in the study cohort including 1,064 AJCC stage and 336 breast subtypes. The demographic and clinical characteristics of these patients are listed in Table 1.

The study included 7,771 female (98.9%) and 85 male (1.1%) patients. The median age was 64 years (range, 15–100 years). Most patients were aged ≥60 years (n=5,914, 75.3%) (Table 1). White patients accounted for 82.1%, and most were widowed (n=2,960, 37.7%; Figure 1). According to the histological type, most of the tumors were neoplasms (n=7,676, 97.7%). Based on the numbers of patients from different states in the United States, California was the most common registration location (37.2%) (Figure 2). The first choice of treatment for patients with NECB was surgery of primary tumor. Surgery was performed in 2,251 (28.7%) cases, no cancer cause surgery in 1,419 (18.1%) cases, radiation in 613 (7.8%) cases, chemotherapy in 981 cases, and surgery combined with radiation therapy in 527 (6.7%) cases. Stage IV accounted for 54.6% and the subtype of HR+/HER2− contributed more than half of the proportion. As for the time of data collection, 3,460 (44.0%) patients either were either alive or dead from other causes, and 4,396 (56.0%) were dead due to NECB.

Figure 1 Marital status distribution of the patients.

Figure 2 Distribution of patients with different pathological types.

Survival analysis

The CSS rates at 3, 5, 8, 10 years were 53.0%, 48.9%, 46.0%, and 45.0%, respectively. A Kaplan-Meier curve was constructed to illustrate the CSS values for the entire cohort (Figure 3A). The log-rank test indicated that the following variables were possibly related to CSS: age at diagnosis (Figure 3B), sex (Figure 3C), race (Figure 3D), marital status (Figure 3E), histological type (Figure 3F), registration location (Figure 3G), surgery of primary tumor (Figure 3H) surgery combined with radiation (Figure 3I), no cancer cause surgery (Figure 3J), radiation (Figure 3K), chemotherapy (Figure 3L), AJCC stage (Figure 3M) and breast subtype (Figure 3N). The results of multivariate Cox proportional hazard regression analysis indicated that there were extraordinarily significant differences in age, marital status, registration location, surgery of primary tumor, no cancer cause surgery, AJCC stage and breast subtype in patients with NECB. The results also showed that surgical treatment including surgery of primary tumor, surgery combined with radiation, and no cancer cause surgery, were all effective in improving the prognosis compared with not providing surgical treatment. The results produced by the log-rank test and the univariate and multivariate Cox proportional-hazards models are listed in Tables 2-4, respectively.

Figure 3 Kaplan-Meier survival analysis. The overall survival of the entire cohort (A). The survival analysis of patients classified based on age at diagnosis (B), sex (C), race (D), marital status (E), histological type according to WHO classification (F), state of registration (G), surgery of primary tumor (H), surgery combined with radiation (I), no cancer cause of surgery (J), radiation (K), chemotherapy (L), AJCC stage (M), breast subtype (N). HR, hormone receptor; HER2, human epidermal growth factor receptor-2; WHO, World Health Organization; AJCC, American Joint Committee on Cancer.

Discussion

Primary NECB is an uncommon and underrecognized subtype of breast carcinoma. Neuroendocrine carcinomas of the breast occur mainly in postmenopausal women (2). According to the results of the current study, patients aged ≥60 years accounted for most of the cases (n=5,914, 75.3%). NECB is rare, and with the incidence rates of 5/1,845 (0.27%) and 7/1,368 (0.5%) reported in two previous studies (8,9). In the current study, the number of NECB cases was 12,263, accounting for 1.07% of all mammary neoplasms, which was close to the largest number of neuroendocrine tumors of the breast in recent studies.

Classification, stage and subtype

In 2003, the WHO classified NECB into three groups: (I) solid neuroendocrine carcinoma, (II) small-cell carcinoma/oat cell carcinoma, and (III) large-cell neuroendocrine carcinoma (6). The 2012 WHO classification (10) subsequently defined NECB as neuroendocrine markers being expressed in >50% of a specimen (chromogranin and synaptophysin were the most common, but had no unique features on mammography and ultrasound) (11,12). We collected data from the SEER database during 2000–2017, and the classification of NECB in 2003 is more detailed than that in 2012. Hence, we used the 2003 WHO classification. We found that most subtypes were solid neuroendocrine carcinoma, which comprised 7,676 cases (97.7%). No significant difference was therefore found in molecular typing. According to the types and proportions of expressed neuroendocrine markers, solid neuroendocrine carcinoma was also a group with heterogeneous tumors. For example, the expressions of HR including estrogen receptor (ER) and progesterone receptor (PR), and HER2 in breast cancer can be used to distinguish molecular typing and to select different treatment plans. According to the different markers expressed by tumors, the selection of different corresponding treatment methods may be effective in improving the prognosis of NECB. In the research, it was discovered that stage and subtype are independent prognostic factors of breast neuroendocrine carcinoma which is consistent with the previous study (3). Although NECB is rare, its prognosis is similar to that of other types of breast cancer, which is affected by clinical staging and tumor molecular typing (13,14).

Race, radiation, chemotherapy, and surgery combined with radiation

The combination of race, radiation, chemotherapy, and surgery combined with radiation was significant in the univariate Cox and Kaplan-Meier analyses but not in the multivariate Cox analysis. A previous study that analyzed the same data obtained different results when applying three different statistical methods (15). The first reason for this discrepancy may be a spurious association between exposure and outcome. For example, when we studied the association between carrying a cigarette lighter and lung cancer, smoking was a confounding factor associated with both of these variables, resulting in a “false association” between them. Controlling smoking in a multivariate analysis resulted in the identified “false association” disappearing. Race may similarly be a false association factor, and differences in the acceptance of treatment concepts by people from different racial groups may lead to different outcomes, rather than due to race itself. This is because race is a complex social construct that encompasses various factors, including cultural beliefs, socioeconomic status, and access to healthcare. Therefore, in future research, the true correlation between race and outcomes can be determined by controlling these confounding factors. NECB was found to not be sensitive to radiotherapy and chemotherapy (16,17). The second possible reason is that exposure is indirectly associated with outcome, and these factors are indirectly associated with NECB prognosis. For example, hypoglycemic drugs cause blood glucose changes by changing insulin levels, and no correlation has been found between hypoglycemic drugs and blood glucose under the condition that the insulin level remains constant. The third possibility is the influence of the small of the sample, since only 7.8%, 12.5%, and 6.7% of patients received radiotherapy, chemotherapy, and surgery combined with radiation, respectively.

Surgery

The classification of surgical data provided by the SEER database made it difficult to obtain the specific surgical method and scope. We could therefore only simply divide patients into two groups: (I) receiving surgical treatment and (II) not receiving surgical treatment. Survival analysis found that patients who underwent either in-situ surgery or surgery for non-tumor-related reasons had better outcomes. This was consistent with previous results for other types of breast cancer treatment (18). Besides, although surgery for non-tumor-related reasons may not directly hinder tumor development, it can improve patients’ quality of life (19). As we know, mood is an important factor influencing the development of breast cancer (20). For NECB patients who also have other diseases, prioritizing treatment of other diseases can effectively improve the emotion of NECB patients, enhance patients’ confidence in life, indirectly inhibit the growth of NECB tumor, and improve patients’ survival. Timing is sometimes considered, but surgery is still essential (21). Radical surgery is still the first choice to improve the prognosis of breast cancer (22).

Marital status

Marital status has been extensively studied in relation to cancer survival, and the findings are subject to ongoing debate and inconclusive hypotheses (23-25). While it has been observed that unmarried women face a higher risk of mortality compared to married women, indicating that the importance of spousal companionship and support during breast cancer recovery, which was also demonstrated in males, the exact impact of marital status on prognosis remains uncertain (26). Single and widowed patients are considered to be in high-risk groups, which was also confirmed in our study. There are several possible explanations for this. First of all, married patients experience less distress and depression compared with unmarried and widowed patients. A partner can not only share the emotional burden but also provide appropriate social support (27). Chronic stress and loneliness can down-regulate cellular immune responsibility (28), stimulate tumor angiogenesis (29), and increase tumor load and aggressiveness. Moreover, patients receive emotional and financial support from their partners (30,31). Emotional support may increase the sense of well-being and belief that patients with cancer have about their treatment, and reduce their mortality risk (32). Furthermore, marital status has been associated with disparities in early cancer diagnoses (33). Previous results suggested that married patients are more likely to receive earlier clinical diagnoses, which generally correspond to better prognoses (34,35), whereas unmarried patients often face delays in diagnosis and may not receive adequate treatment (36). These factors highlight the potential role of maintaining a good marital relationship can therefore improve the prognosis of patients with NECB. However, it is important to acknowledge that the relationship between marital status and prognosis is a complex issue with conflicting findings. For instance, Li et al. (33) found significant survival differences only for single individuals with stages III–IV compared to married individuals, while no significant differences are observed for other stages and marital status. These discrepancies warrant further investigation and caution in making definitive statements regarding the direct influence of marital status on prognosis. In summary, while studies have shown associations between marital status and cancer survival, the exact impact remains contentious. Marital status may influence psychological well-being, access to support, and timely diagnosis, all of which can indirectly affect prognosis. Nevertheless, further research is needed to fully understand the underlying mechanisms and establish a conclusive relationship between marital status and the prognosis of patients with NECB.

Registration location

The prognoses of Alaska Natives were much better than that of patients in other areas. Alaska Natives have a low prevalence rate and a high survival rate. In our study, only one of the eight patients collected from this population died, giving a survival rate of 87.5%. Alaska Natives comprise 14% of the population, of which 20–25% come from rural communities (37). On the one hand, they experience poverty and inadequate food supply, but on the other hand (38), they have a good ecological environment without urban pollution. Alaska is close to the Arctic, where people enjoy a natural marine climate, fresh air, and have little anxiety and work stress (39). These are the probable reasons for their low morbidity and high survival rate.

Strengths and limitations

To our knowledge, our study represents one of the largest population-based studies to estimate the prognosis of NECB, providing a strong insight into the prognosis of patients with NECB. However, several limitations of our research are also apparent on the paper. First, gaps in the information available about the scope and method of surgery meant that we could not confirm how the specific surgical method and its duration affected survival. Second, information about chemoradiotherapy was insufficient. The chemotherapy and radiotherapy statuses are uncertain for some patients in the SEER data, which may lead to misclassification. Third, this study was a retrospective analysis, which may therefore have been biased. The data were collected by many different people, which may have caused certain subjective differences and the possibility of inaccurate data. Notwithstanding these limitations, this study had strengths of being based on real-world population data. NECB is a rare form of breast cancer, and recording such a large amount of data is difficult. This study provides useful information for improving the understanding of the epidemiological characteristics and survival rate of NECB.

Conclusions

NECB is a rarely seen lesion, accounting for only 1.07% of breast cancers. Age, marital status, registration location, surgery, AJCC stage and breast subtype were found to be its independent prognostic factors.

Acknowledgments

Funding: This work was supported by National Natural Science Foundation of China (No. 81871943 to JC); Guangdong Provincial Clinical Research Center for Digestive Diseases (No. 2020B1111170004); Guangzhou High-level Key Clinical Specialty Construction Project (No. 9); and The Project of Key Medical Discipline in Guangzhou (No. 2021-2023).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-368/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-368/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-368/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The SEER Program has a strict policy to protect patient privacy, and all data were de-identified prior to analysis. No informed consent was required for this retrospective study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Gallo M, Campione S, Di Vito V, et al. Primary Neuroendocrine Neoplasms of the Breast: Still Open Issues. Front Endocrinol (Lausanne) 2021;11:610230. [Crossref] [PubMed]
2. Rosen LE, Gattuso P. Neuroendocrine Tumors of the Breast. Arch Pathol Lab Med 2017;141:1577-81. [Crossref] [PubMed]
3. Wang J, Wei B, Albarracin CT, et al. Invasive neuroendocrine carcinoma of the breast: a population-based study from the surveillance, epidemiology and end results (SEER) database. BMC Cancer 2014;14:147. [Crossref] [PubMed]
4. Cheymol C, Abramovici O, Do Cao C, et al. Neuroendocrine tumors of the breast: Myth or reality? A systematic review. Bull Cancer 2018;105:431-9. [Crossref] [PubMed]
5. Li Y, Du F, Zhu W, et al. Neuroendocrine carcinoma of the breast: a review of 126 cases in China. Chin J Cancer 2017;36:45. [Crossref] [PubMed]
6. Tavassoli FA, Devilee P. Pathology and Genetics of Tumours of the Breast and Female Genital Organs. Lyon: IARC Press; 2003.
7. Cronin KA, Ries LA, Edwards BK. The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. Cancer 2014;120:3755-7. [Crossref] [PubMed]
8. López-Bonet E, Alonso-Ruano M, Barraza G, et al. Solid neuroendocrine breast carcinomas: incidence, clinico-pathological features and immunohistochemical profiling. Oncol Rep 2008;20:1369-74. [PubMed]
9. Günhan-Bilgen I, Zekioglu O, Ustün EE, et al. Neuroendocrine differentiated breast carcinoma: imaging features correlated with clinical and histopathological findings. Eur Radiol 2003;13:788-93. [Crossref] [PubMed]
10. Lakhani SR, Ellis IO, Schnitt SJ, et al. WHO Classification of Tumours of the Breast. 4th edition. Lyon: IARC Press; 2012.
11. Adams RF, Parulekar V, Hughes C, et al. Radiologic characteristics and management of screen-detected metastatic carcinoid tumor of the breast: a case report. Clin Breast Cancer 2009;9:189-92. [Crossref] [PubMed]
12. Fujimoto Y, Yagyu R, Murase K, et al. A case of solid neuroendocrine carcinoma of the breast in a 40-year-old woman. Breast Cancer 2007;14:250-3. [Crossref] [PubMed]
13. Laé M, Fréneaux P, Sastre-Garau X, et al. Secretory breast carcinomas with ETV6-NTRK3 fusion gene belong to the basal-like carcinoma spectrum. Mod Pathol 2009;22:291-8. [Crossref] [PubMed]
14. Cloyd JM, Yang RL, Allison KH, et al. Impact of histological subtype on long-term outcomes of neuroendocrine carcinoma of the breast. Breast Cancer Res Treat 2014;148:637-44. [Crossref] [PubMed]
15. George B, Seals S, Aban I. Survival analysis and regression models. J Nucl Cardiol 2014;21:686-94. [Crossref] [PubMed]
16. Inno A, Bogina G, Turazza M, et al. Neuroendocrine Carcinoma of the Breast: Current Evidence and Future Perspectives. Oncologist 2016;21:28-32. [Crossref] [PubMed]
17. Shinohara ET, Maity A. Increasing sensitivity to radiotherapy and chemotherapy by using novel biological agents that alter the tumor microenvironment. Curr Mol Med 2009;9:1034-45. [Crossref] [PubMed]
18. Magnoni F, Galimberti V, Corso G, et al. Axillary surgery in breast cancer: An updated historical perspective. Semin Oncol 2020;47:341-52. [Crossref] [PubMed]
19. Jitender S, Mahajan R, Rathore V, et al. Quality of life of cancer patients. J Exp Ther Oncol 2018;12:217-21. [PubMed]
20. Wang X, Wang N, Zhong L, et al. Prognostic value of depression and anxiety on breast cancer recurrence and mortality: a systematic review and meta-analysis of 282,203 patients. Mol Psychiatry 2020;25:3186-97. [Crossref] [PubMed]
21. Su Y, Zheng X, Ouyang Z. The Relationship between Time to Surgery (TTS) and Survival in Breast Cancer: A Systematic Review and Meta-Analysis. Iran J Public Health 2021;50:1773-82. [Crossref] [PubMed]
22. Maughan KL, Lutterbie MA, Ham PS. Treatment of breast cancer. Am Fam Physician 2010;81:1339-46. [PubMed]
23. Song W, Tian C. The Effect of Marital Status on Survival of Patients with Gastrointestinal Stromal Tumors: A SEER Database Analysis. Gastroenterol Res Pract 2018;2018:5740823. [Crossref] [PubMed]
24. Ruvolo CC, Nocera L, Stolzenbach FL, et al. Contemporary analysis of the effect of marital status on survival in upper tract urothelial carcinoma patients treated with radical nephroureterectomy: A population-based study. Urol Oncol 2021;39:789.e9-789.e17. [Crossref] [PubMed]
25. Xiao K, Zhao Y, Cai Y, et al. The effect of marital status on the survival of patients with colorectal neuroendocrine neoplasms: an analysis of the SEER database. Rev Esp Enferm Dig 2020;112:109-17. [PubMed]
26. Liu L, Chi YY, Wang AA, et al. Marital Status and Survival of Patients with Hormone Receptor-Positive Male Breast Cancer: A Surveillance, Epidemiology, and End Results (SEER) Population-Based Study. Med Sci Monit 2018;24:3425-41. [Crossref] [PubMed]
27. Kaiser NC, Hartoonian N, Owen JE. Toward a cancer-specific model of psychological distress: population data from the 2003-2005 National Health Interview Surveys. J Cancer Surviv 2010;4:291-302. [Crossref] [PubMed]
28. Pike JL, Irwin MR. Dissociation of inflammatory markers and natural killer cell activity in major depressive disorder. Brain Behav Immun 2006;20:169-74. [Crossref] [PubMed]
29. Antoni MH, Lutgendorf SK, Cole SW, et al. The influence of bio-behavioural factors on tumour biology: pathways and mechanisms. Nat Rev Cancer 2006;6:240-8. [Crossref] [PubMed]
30. Dickens C, McGowan L, Percival C, et al. Depression is a risk factor for mortality after myocardial infarction: fact or artifact? J Am Coll Cardiol 2007;49:1834-40. [Crossref] [PubMed]
31. Anderson JC, Fortinsky RH, Kleppinger A, et al. Predictors of compliance with free endoscopic colorectal cancer screening in uninsured adults. J Gen Intern Med 2011;26:875-80. [Crossref] [PubMed]
32. Gonzales FA, Hurtado-de-Mendoza A, Santoyo-Olsson J, et al. Do coping strategies mediate the effects of emotional support on emotional well-being among Spanish-speaking Latina breast cancer survivors? Psychooncology 2016;25:1286-92. [Crossref] [PubMed]
33. Li X, Liu Y, Wang Y, et al. The influence of marital status on survival of gallbladder cancer patients: a population-based study. Sci Rep 2017;7:5322. [Crossref] [PubMed]
34. Yu B, Lin F, Duan J, et al. The influence of marital status on survival in patients with nasopharyngeal carcinoma: A surveillance, epidemiology, and end results database analysis. Medicine (Baltimore) 2022;101:e30516. [Crossref] [PubMed]
35. Krajc K, Miroševič Š, Sajovic J, et al. Marital status and survival in cancer patients: A systematic review and meta-analysis. Cancer Med 2023;12:1685-708. [Crossref] [PubMed]
36. Aizer AA, Chen MH, McCarthy EP, et al. Marital status and survival in patients with cancer. J Clin Oncol 2013;31:3869-76. [Crossref] [PubMed]
37. Alaska Department of Health and Social Services (DHSS): behavioral health performance review. Available online: http://library.state.ak.us/asp/edocs/2015/12/ocn932260266.pdf
38. Walch A, Loring P, Johnson R, et al. A scoping review of traditional food security in Alaska. Int J Circumpolar Health 2018;77:1419678. [Crossref] [PubMed]
39. Walsh JE. Climate of the Arctic marine environment. Ecol Appl 2008;18:S3-22. [Crossref] [PubMed]