The relationship between marital status and survival in primary bone cancer: a population-based study

Introduction

Primary bone cancer are rare and often highly malignant, posing a severe threat to patients’ quality of life and survival (1,2). It is estimated that in 2024, there will be 3,970 new cases and 2,050 deaths in the United States (3). Despite their rarity, the incidence of primary malignant bone cancer is significantly stratified by age, being the third most common type of cancer among individuals under the age of 19, following brain/other nervous system (ONS) tumors and leukemia (3). The therapeutic options for primary bone cancer are relatively constrained, primarily consisting of surgical resection, radiotherapy, and chemotherapy (2,4). Given the diverse biological behaviors of bone cancer and their generally low sensitivity to radiochemotherapy, many challenges are encountered in treatment. Despite advancements in multimodal therapies in recent years, the prognosis for patients remains unsatisfactory; for instance, the 5-year survival rate for patients with osteosarcoma is less than 70% (5).

In recent years, an increasing number of studies have found that marital status is associated with the prognosis of various malignant tumors (6-16). This may be related to married patients being more likely to receive social support, more standardized treatment, and leading healthier lifestyles (17). However, in the special group of primary malignant bone cancer, the impact of marital status on prognosis has not been fully explored, which to some extent limits our understanding of the comprehensive management of patients with primary bone cancer. Investigating the impact of marital status on the prognosis of patients with primary malignant bone cancer has significant practical implications. Analyzing the impact of marital status on cancer prognosis not only aids in developing personalized treatment strategies and enhancing clinicians’ understanding of prognostic factors but also enables the provision of tailored psychological and social support, ultimately aiming to elevate the quality of life for patients and their families. Furthermore, such research contributes valuable data that can guide public health strategies, potentially optimizing medical resource distribution and enhancing overall outcomes for cancer patients (17).

Given the rarity of primary bone cancer, the Surveillance, Epidemiology, and End Results (SEER) database offers a crucial resource for extensive analysis due to its large and comprehensive dataset. In this study, leveraging the SEER database, we investigated the impact of marital status on the prognosis of patients with primary bone cancer, aiming to uncover potential correlations that could inform patient care and therapeutic strategies. We present this article in accordance with the STROBE reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1215/rc).

Methods

Data source and inclusion criteria

Established by the National Cancer Institute, SEER is a comprehensive cancer surveillance system that meticulously records cancer incidence, prevalence, and survival data. The program encompasses a collection of geographically defined, population-based tumor registries, which together represent half of the United States population. Specifically, the SEER-17 dataset spanning the years 2000 to 2020 was employed for this study, covering approximately 26.5% of the total U.S. population. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

The patient selection process is depicted in Figure 1. We utilized the International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3), to identify patients with primary bone cancer, categorized under codes C40 and C41. Inclusion criteria were set to encompass patients above the age of 20. Patients with incomplete data regarding sociodemographic factors—such as race, ethnicity, median household income, residential area, and marital status—as well as those with unknown oncological outcomes [cancer-specific survival (CSS) and overall survival (OS) rates] were excluded from this study. The study employed the SEER Summary Stage (2004+) to categorize patient staging, which includes localized, regional, and distant stages. Patients with unstaged tumors according to the SEER Summary Stage (2004+) were also excluded. Furthermore, since the SEER Summary Stage (2004+) is only available from 2004 onwards, the study included patients diagnosed within the 2004–2020 timeframe.

Figure 1 Flowchart of patient screening. SEER, Surveillance, Epidemiology, and End Results.

Variable processing and statistical analysis

Given the rarity of primary bone cancer, to prevent the issue of insufficient sample size in any subgroup that might affect subsequent statistical analysis, we initially consolidated the multi-categorical variables. Specifically, the median household income (adjusted to the year 2021), which included <35,000 United States dollar (USD), 35,000–39,999 USD, 40,000–44,999 USD, 45,000–49,999 USD, 50,000–54,999 USD, 55,000–59,999 USD, 60,000–64,999 USD, 65,000–69,999 USD, 70,000–74,999 USD, and 75,000+ USD, was divided into two categories based on the income threshold of less than 75,000 USD and equal to or greater than 75,000 USD. Race, comprising White, Black, Asian, or Pacific Islander, American Indian/Alaska Native, was categorized into White and non-White. The histology of primary bone cancer is diverse (4). Given that osteosarcoma and Ewing’s sarcoma are the two most common types, we categorized the histologies into osteosarcoma/Ewing’s sarcoma (codes 9180–9186, 9192–9194 for osteosarcoma, code 9260 for Ewing’s sarcoma) and others. Marital status, as recorded in the SEER and including married, single, separated, divorced, widowed, and unmarried or domestic partner, was aggregated into married and unmarried (encompassing single, separated, divorced, widowed, and unmarried or domestic partner) based on previous research. Additionally, for ease of statistical analysis, age was dichotomized based on its median value of 53 years.

After variable processing, the Pearson’s chi-squared test was employed to examine the differences in baseline characteristics between married and unmarried patients. The primary oncological outcomes of interest in this study were OS and CSS. Kaplan-Meier curves and the Log-rank test were utilized to evaluate the differences in CSS and OS between the two groups. Subsequently, to mitigate the impact of baseline disparities on survival, a 1:1 propensity score matching (PSM) was conducted. Post-PSM, the influence of gender on CSS and OS was reassessed using Kaplan-Meier curves and the Log-rank test. Considering a previous study that reported a gender difference in the protective effect of marriage, we also performed a subgroup analysis based on gender (6). Finally, a multivariate Cox regression analysis was conducted to ascertain the independent impact of gender on CSS and OS, adjusting for covariates including age, year of diagnosis, sex, race, ethnicity, median household income, place of residence, histological type, tumor grade, tumor stage, treatment modality (surgery and chemotherapy). All variables were included in the multivariate Cox regression model, irrespective of their significance in the univariate Cox regression analysis. All statistical analyses in this study were performed using R software (version 4.3.0). All P values were two-tailed, with a significance threshold set at 0.05.

Results

Patient baseline characteristics

Table 1 presents the demographic and baseline characteristics of patients before and after PSM. A total of 8,208 patients with primary malignant bone cancer were included in this study, comprising 4,650 married and 3,558 unmarried patients. The majority of the patients were male (55.5%), White (83.4%), Non-Spanish-Hispanic-Latino (82.8%), had a median household income less than 75,000 USD (56.3%), resided in urban areas (89.6%), and did not have osteosarcoma/Ewing’s sarcoma (71.1%). Most patients underwent surgical treatment and had unknown or did not receive chemotherapy. The distribution of tumor grades was 26.3% for grade I–II, 24.6% for grade III–IV, and 49.1% unknown. Tumor stages were distributed as localized in 44.9%, regional in 35.8%, and distant in 19.3% of the total population. Before matching, significant differences were observed between married and unmarried patients in terms of age (P<0.001), sex (P<0.001), race (P<0.001), ethnicity (P=0.001), median household income (P=0.004), histology (P<0.001), tumor grade (P<0.001), surgery (P<0.001), and chemotherapy (P<0.001). All variables considered in the PSM were adjusted. After matching, each group consisted of 3,138 patients, and all baseline characteristics were balanced between the two groups.

OS and CSS

As depicted in Figure 2, prior to PSM, married patients exhibited significantly better OS compared to unmarried patients [hazard ratio (HR) =0.93, 95% confidence interval (CI): 0.87–0.99, P=0.047, Figure 2A]. However, the difference in CSS between the two groups was not statistically significant (HR =0.95, 95% CI: 0.88–1.03, P=0.21, Figure 2B). Table 2 presents Kaplan-Meier estimates of 1-, 3-, 5-, and 10-year OS and CSS rates for married and unmarried patients with primary bone cancer before and after PSM. The 1-, 3-, 5-, and 10-year OS rates for unmarried and married patients were 80.2% (95% CI: 78.8–81.5%), 65.2% (95% CI: 63.6–66.9%), 58.5% (95% CI: 56.7–60.3%), and 49.0% (95% CI: 47.1–51.1%) compared to 82.1% (95% CI: 81.0–83.2%), 67.4% (95% CI: 66.0–68.8%), 61.1% (95% CI: 59.6–62.7%), and 51.3% (95% CI: 49.6–53.1%), respectively. The 1-, 3-, 5-, and 10-year CSS rates for unmarried and married patients were 85.0% (95% CI: 83.8–86.2%), 72.4% (95% CI: 70.8–74.0%), 67.0% (95% CI: 65.2–68.7%), and 61.2% (95% CI: 59.3–63.2%) compared to 86.1% (95% CI: 85.1–87.2%), 73.8% (95% CI: 72.5–75.2%), 68.9% (95% CI: 67.4–70.4%), and 62.7% (95% CI: 61.0–64.4%), respectively. Following PSM, married patients demonstrated improved OS (HR =0.85, 95% CI: 0.79–0.92, P<0.001, Figure 3A) and CSS (HR =0.92, 95% CI: 0.84–0.99, P=0.045, Figure 3B) compared to unmarried patients. The 1-, 3-, 5-, and 10-year OS rates for unmarried and married patients were 80.6% (95% CI: 79.2–82.0%), 65.5% (95% CI: 63.8–67.3%), 58.6% (95% CI: 56.7–60.5%), and 48.8% (95% CI: 46.8–51.0%) compared to 83.8% (95% CI: 82.5–85.2%), 69.1% (95% CI: 67.4–70.8%), 62.9% (95% CI: 61.0–64.8%), and 54.6% (95% CI: 52.6–56.7%), respectively. The 1-, 3-, 5-, and 10-year CSS rates for unmarried and married patients were 85.5% (95% CI: 84.2–86.8%), 72.9% (95% CI: 71.2–74.6%), 67.4% (95% CI: 65.6–69.3%), and 61.6% (95% CI: 59.6–63.8%) compared to 87.3% (95% CI: 86.1–88.5%), 74.6% (95% CI: 73.0–76.3%), 69.6% (95% CI: 67.9–71.5%), and 64.0% (95% CI: 61.9–66.0%), respectively. Married patients exhibited better OS and CSS at all time points compared to unmarried patients (Table 2). In gender-based subgroup analyses for OS, male patients did not benefit from marriage (HR =0.98, 95% CI: 0.88–1.10, P=0.78, Figure 4A), whereas female patients experienced a significant survival benefit (HR =0.73, 95% CI: 0.65–0.81, P<0.001, Figure 4B). Similar to OS, for CSS, there was no benefit observed for male patients in relation to marriage (HR =1.03, 95% CI: 0.91–1.16, P=0.68, Figure 4C), while female patients had a significant survival benefit (HR =0.81, 95% CI: 0.70–0.93, P=0.002, Figure 4D).

Figure 2 Pre-matching analysis depicting the (A) overall survival and (B) cancer-specific survival rates using Kaplan-Meier curves. HR, hazard ratio; CI, confidence interval.

Figure 3 Post-matching analysis depicting the (A) overall survival and (B) cancer-specific survival rates using Kaplan-Meier curves. HR, hazard ratio; CI, confidence interval.

Figure 4 Kaplan-Meier curves for overall survival in male (A) and female (B) patients, as well as cancer-specific survival in in male (C) and female (D) patients. HR, hazard ratio; CI, confidence interval.

The results of the Cox regression are presented in Table 3. In the multivariate Cox regression analysis, the following factors were identified as independent predictors for OS: age (>53 vs. 21–53 years: HR =2.66, 95% CI: 2.44–2.91, P<0.001), sex (female vs. male: HR =0.86, 95% CI: 0.80–0.93, P<0.001), median household income (≥75,000 USD vs. <75,000 USD: HR =0.92, 95% CI: 0.84–0.99, P=0.04), marital status (married vs. unmarried: HR =0.86, 95% CI: 0.79–0.93, P<0.001), histology (other types vs. osteosarcoma/Ewing sarcoma: HR =0.77, 95% CI: 0.70–0.86, P<0.001), tumor grade (grade III–IV vs. grade I–II: HR =2.44, 95% CI: 2.14–2.78, P<0.001; unknown vs. grade I–II: HR =1.47, 95% CI: 1.30–1.66, P<0.001), tumor stage (regional vs. localized: HR =1.47, 95% CI: 1.34–1.62, P<0.001; distant vs. localized: HR =3.64, 95% CI: 3.26–4.07, P<0.001), and surgery (not performed vs. performed: HR =2.58, 95% CI: 2.35–2.82, P<0.001). Independent predictors of CSS include: age (>53 vs. 21–53 years: HR =2.13, 95% CI: 1.92–2.36, P<0.001), sex (female vs. male: HR =0.85, 95% CI: 0.78–0.94, P<0.001), marital status (married vs. unmarried: HR =0.91, 95% CI: 0.82–0.97, P=0.04), histology (other types vs. osteosarcoma/Ewing sarcoma: HR =0.71, 95% CI: 0.63–0.79, P<0.001), tumor grade (grade III–IV vs. grade I–II: HR =2.96, 95% CI: 2.51–3.49, P<0.001; unknown vs. grade I–II: HR =1.68, 95% CI: 1.44–1.96, P<0.001), tumor stage (regional vs. localized: HR =1.64, 95% CI: 1.45–1.85, P<0.001; distant vs. localized: HR =4.61, 95% CI: 4.04–5.26, P<0.001), and surgery (not performed vs. performed: HR =2.45, 95% CI: 2.20–2.73, P<0.001).

Discussion

Marriage has been proven to improve outcomes in various malignant tumors, such as prostate cancer, lung cancer, breast cancer, renal cell carcinoma, colorectal cancer, esophageal cancer, head and neck cancer, liver/intrahepatic cholangiocarcinoma, and non-Hodgkin’s lymphoma, etc. (6-16). In a previous study based on the SEER database, Aizer et al. included over 1.2 million patients diagnosed with 10 common types of cancer and found that compared to unmarried patients, married patients were less likely to develop metastatic disease [odds ratio (OR) =0.83; 95% CI: 0.82–0.84; P<0.001], more likely to receive definitive treatment (OR =1.53; 95% CI: 1.51–1.56; P<0.001), and less likely to die from cancer (HR =0.80; 95% CI: 0.79–0.81; P<0.001). Furthermore, the survival benefit attributed to marriage in prostate, breast, colorectal, esophageal, and head and neck cancers exceeded that reported for chemotherapy (6). Chen et al. explored the mediating factors between marriage and prognosis in another study that included over 1.7 million patients diagnosed with nine common types of malignant tumors. They found that early diagnosis partly mediated the association between marital status and CSS in breast cancer, colorectal cancer, endometrial cancer, and melanoma. While treatment-related variables partly mediated the association between marital status and CSS in lung cancer, pancreatic cancer, and prostate cancer (17).

The health-protective effect of marriage is not limited to cancer (18-20). In a meta-analysis involving over 7.8 million people, marriage was identified as significantly correlated with lower all-cause mortality, cancer mortality, cardiovascular disease mortality, and coronary heart disease mortality (18). In another meta-analysis of 38 studies on frailty in community-dwelling older adults, marriage was significantly associated with a lower risk of frailty (19). Additionally, marriage is also related to a significantly reduced risk of dementia (20). These studies clarify the protective effect of marriage on health at multiple levels, which may be driven by various factors (6,17-20). On the one hand, married patients may have better social and emotional support, thereby affecting their access to healthcare, improving treatment compliance, and quality of life (6,17). On the other hand, married patients may be more inclined to adopt healthy behaviors, such as quitting smoking and regular check-ups, which may positively affect the prognosis (18-20).

Understanding how marital status affects survival outcomes is crucial for improving patient care. This can help medical professionals identify patient groups that may need additional support and provide them with customized interventions. In the field of bone cancer, to our knowledge, only one study has conducted relevant research (21). In that study, patients categorized by marital status showed significant differences in early-stage cancer diagnosis, surgery rates, and overall and disease-specific mortality risks. However, the study was limited by its inclusion of patients aged 40 and above, lacking representativeness, and potential baseline differences between groups may have affected survival outcomes (21). In adolescents and young adults (AYA), a group experiencing critical life events such as education, employment, relationships, marriage, and childbirth, marriage may enhance survival rates by providing emotional and social support, improving post-operative adherence and follow-up (22). Additionally, marriage as a psychosocial factor may influence patients’ decision-making processes, especially in this critical period. Married patients might be more inclined towards early and aggressive surgical treatment, driven by spousal encouragement to seek timely medical attention and strictly follow treatment plans. Therefore, investigating the protective role of marriage across all age groups is essential to deepen our understanding of its role in sarcoma patients’ outcomes.

In our study, PSM was used to balance baseline characteristics, significantly reducing potential bias. Before PSM, marriage significantly improved OS (HR =0.93, 95% CI: 0.87–0.99, P=0.047), but not CSS (HR =0.95, 95% CI: 0.88–1.03, P=0.21). After PSM fully balanced baseline characteristics, marriage significantly improved both OS (HR =0.85, 95% CI: 0.79–0.92, P<0.001) and CSS (HR =0.92, 95% CI: 0.84–0.99, P=0.045). This is consistent with research in other malignant tumors (6-16). In subgroup analysis, an interesting phenomenon was observed: the positive impact of marital status on survival was more pronounced in females, while no similar benefit was observed in males. This is inconsistent with research results in other tumor types, where males usually benefit more from marriage. Although the reasons for this are not entirely clear, these findings highlight that marital status may affect health outcomes differently across sex and disease types, an understanding that is critical for developing social policies, medical interventions, and personalized patient care plans.

The strengths of this study include the large sample size from the SEER database and the use of PSM to control for baseline differences, enhancing the reliability of the results. However, as a retrospective study, potential selection bias and information bias may be present.

Conclusions

In summary, marriage has a protective effect on OS and CSS in patients with primary bone cancer, however, this effect only exists in women but not in men. Future studies should further explore the mechanisms behind this phenomenon and consider how to apply this knowledge in clinical practice to improve the overall prognosis of patients.

Acknowledgments

Our sincere appreciation is extended to the SEER database for offering the essential data that facilitated the completion of this study.

Funding: This work was supported by the Science and Technology Research Program of Sichuan Province, under grant number 2023YFH0099.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1215/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1215/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1215/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).

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/.

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