Introduction
Follicular lymphoma (FL) is the most common indolent subtype of non-Hodgkin lymphoma. Although the disease typically follows a slow clinical course, it is considered incurable in most advanced-stage patients [ 1 ]. Despite frequent relapses, modern immunochemotherapy has significantly prolonged survival, with median survival now exceeding 15 years [ 2 , 3 ]. Several prognostic models have been developed to guide treatment decisions and risk stratification [ 4 ], and while they integrate disease specific variables, they do not account for psychosocial or sociodemographic factors, which also influence outcomes.
Married patients are consistently reported to have superior survival compared with their unmarried counterparts in multiple solid tumors and hematologic malignancies [ 5 – 7 ]. This advantage has been linked to enhanced emotional and financial support, improved treatment adherence, and greater access to healthcare services. In contrast, unmarried patients may be more susceptible to delayed care, under-treatment, and psychosocial distress [ 8 , 9 ]. Although the influence of marital status has been evaluated in other cancers, its prognostic significance has not been systematically assessed in FL. This disease requires not only long-term follow-up but also patient engagement in surveillance and treatment planning [ 10 ], making the presence of a supportive partner potentially important. Given the chronicity and management complexity of FL, understanding the role of social support may offer additional insights into outcome variability among patients with similar biological risk.
In this study, we conducted a population-based analysis using the Surveillance, Epidemiology, and End Results (SEER) database to investigate the relationship between marital status and survival in patients with FL. Our objective was to determine whether marital status serves as an independent prognostic factor in FL and to identify patient populations who may benefit from enhanced psychosocial support during long-term disease management.
Methods
Patient selection
Data were obtained from the SEER Research Data, 17 Registries, November 2024 submission, accessed using SEER*Stat software (version 8.4.5). Cases were identified using the “2.6 Follicular lymphoma” diagnostic code. To ensure consistency with the modern immunochemotherapy era, only patients diagnosed between 2013 and 2022 were included. We included patients aged 18 years or older who were newly diagnosed with histologically confirmed follicular lymphoma. Patients were excluded if they met any of the following criteria: (1) incomplete survival data, (2) diagnosis by autopsy or death certificate only, (3) unknown marital status, (4) missing Ann Arbor stage, (5) unknown race/ethnicity, (6) unknown B symptom status or (7) age younger than 18 years at diagnosis.
Study variables
Consistent with prior studies examining the prognostic impact of marital status in oncology [ 7 , 11 ], marital status at diagnosis was categorized as married or unmarried. The unmarried group included individuals recorded as single (never married), separated, divorced, widowed, or listed as unmarried/domestic partners in the SEER database. Covariates included sex, age at diagnosis, race/ethnicity (White, Black, Other), Ann Arbor stage (I-IV), B symptoms (present or absent), prior cancer history (yes or no), and treatment status (receipt of chemotherapy and/or radiotherapy). A binary variable was created to indicate whether diagnosis occurred before or after 2017, reflecting shifts in first-line treatment practices over time.
To minimize baseline differences between marital status groups, 1:1 nearest-neighbor propensity score matching without replacement was performed using a caliper width of 0.2. Logistic regression was used to estimate the propensity score with marital status (married vs unmarried) as the grouping variable. Covariates included in the model were age, sex, race, Ann Arbor stage, B symptoms, treatment status, prior cancer history, and diagnosis year (pre-2017 vs post-2017). Covariate balance before and after matching was assessed using standardized mean differences (SMD), with SMD < 0.1 indicating adequate balance, thereby ensuring that the matched cohort comprised married and unmarried patients with comparable baseline characteristics.
Survival analysis
Overall survival (OS) was defined as the time from diagnosis to death from any cause or last follow-up. Cause-specific survival (CSS) was defined as the time from diagnosis to death attributable to follicular lymphoma, based on the SEER cause-specific death classification.
Statistical analysis
Categorical variables were compared using the Chi-squared test or Fisher’s exact test. Kaplan–Meier curves were used to estimate survival, and differences between groups were evaluated using the log-rank test. Univariable and multivariable Cox proportional hazards models were applied to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for relevant covariates. All statistical analyses were conducted using R software (version 4.2.1; R Foundation for Statistical Computing, Vienna, Austria). A two-sided P value < 0.05 was considered statistically significant.
Results
Patients
A total of 28,910 patients diagnosed with follicular lymphoma between 2013 and 2022 were included. Patients were subsequently excluded for the following reasons: unknown race ( n = 267), missing Ann Arbor stage ( n = 1,817), unknown B symptom status ( n = 3,252), and missing or unknown cause of death ( n = 70). Additionally, individuals younger than 18 years at diagnosis ( n = 70) were excluded. The final analytic cohort comprised 23,434 patients, of whom 15,047 (64.2%) were married and 8,387 (35.8%) were unmarried.
Baseline demographic and clinical characteristics stratified by marital status are summarized in otherwise, kindly amend as deemed necessary." Resolved="yes"-->Table 1 . Compared with married patients, unmarried individuals were more likely to be female (60.3% vs. 42.5%, P < 0.001) and older than 60 years at diagnosis (65.5% vs. 63.1%, P < 0.001). A higher proportion of unmarried patients presented with B symptoms (19.9% vs. 17.6%, P < 0.001). In terms of race, unmarried patients were more frequently Black (7.5% vs. 3.2%) and less frequently White (87.0% vs. 89.1%, P < 0.001). No significant differences were observed between groups in Ann Arbor stage, radiotherapy use, year of diagnosis, or prior cancer history ( P > 0.05 for all comparisons).
Table 1
Patient characteristics stratified by marital status
| Characteristic | Total | Marital status | P | |
| ( n = 23434) | Married ( n = 15047) | Unmarried ( n = 8387) | ||
| Sex | < 0.001 | |||
| Female | 11451 (48.9%) | 6395 (42.5%) | 5056 (60.3%) | |
| Male | 11983 (51.1%) | 8652 (57.5%) | 3331 (39.7%) | |
| Age | < 0.001 | |||
| < 60 years | 8440 (36%) | 5548 (36.9%) | 2892 (34.5%) | |
| > 60 years | 14994 (64%) | 9499 (63.1%) | 5495 (65.5%) | |
| B symptoms | < 0.001 | |||
| Absence | 19119 (81.6%) | 12399 (82.4%) | 6720 (80.1%) | |
| Presence | 4315 (18.4%) | 2648 (17.6%) | 1667 (19.9%) | |
| Year of diagnosis | 0.249 | |||
| 2013–2017 | 11648 (49.7%) | 7522 (50%) | 4126 (49.2%) | |
| 2018–2022 | 11786 (50.3%) | 7525 (50%) | 4261 (50.8%) | |
| Race | < 0.001 | |||
| White | 20704 (88.4%) | 13404 (89.1%) | 7300 (87%) | |
| Black | 1103 (4.7%) | 477 (3.2%) | 626 (7.5%) | |
| Other | 1627 (6.9%) | 1166 (7.7%) | 461 (5.5%) | |
| Chemotherapy | 0.002 | |||
| No/unknown | 12665 (54%) | 8021 (53.3%) | 4644 (55.4%) | |
| Yes | 10769 (46%) | 7026 (46.7%) | 3743 (44.6%) | |
| Radiotherapy | 0.296 | |||
| No/unknown | 20049 (85.6%) | 12846 (85.4%) | 7203 (85.9%) | |
| Yes | 3385 (14.4%) | 2201 (14.6%) | 1184 (14.1%) | |
| Ann Arbor stage | 0.244 | |||
| I/II | 9879 (42.2%) | 6386 (42.4%) | 3493 (41.6%) | |
| III/IV | 13555 (57.8%) | 8661 (57.6%) | 4894 (58.4%) | |
| Prior cancer history | 0.444 | |||
| No | 18865 (80.5%) | 12136 (80.7%) | 6729 (80.2%) | |
| Yes | 4569 (19.5%) | 2911 (19.3%) | 1658 (19.8%) |
Survival analysis
Unmarried patients showed significantly worse OS (5-year OS: 72.8% vs. 81.0%; P < 0.001; Fig. 1 A) and CSS (5-year CSS: 84.9% vs. 90.6%; P < 0.001; Fig. 1 B) compared with married patients. Following propensity score matching, baseline characteristics were well balanced between groups, with standardized differences for all covariates below 0.1 (Fig. 2 A). A total of 16,384 patients (8,192 unmarried and 8,192 married) were included in the matched cohort. In the matched cohort, the survival disadvantage for unmarried patients remained significant. Unmarried patients had inferior OS (5-year OS: 72.5% vs. 81.3%; P < 0.001; Fig. 2 B) and CSS (5-year CSS: 84.7% vs. 90.7%; P < 0.001; Fig. 2 C) compared with married patients.
Univariate analysis
On univariate Cox regression, unmarried status was significantly associated with inferior survival compared with married status (OS: HR, 1.52; 95% CI, 1.44–1.61; P < 0.001; CSS: HR, 1.67; 95% CI, 1.54–1.80; P < 0.001). Other factors associated with worse OS and CSS included older age (> 60 years), male sex, presence of B symptoms, advanced Ann Arbor stage, prior cancer history, and diagnosis between 2018–2022. Chemotherapy did not influence OS (HR, 1.01; P = 0.86) but was associated with worse CSS (HR, 1.29; 95% CI, 1.19–1.40; P < 0.001). Radiotherapy was associated with significantly improved survival (OS: HR, 0.64; 95% CI, 0.58–0.70; CSS: HR, 0.52; 95% CI, 0.45–0.60; P < 0.001 for both). Race and year of diagnosis had non-significant effects (Table 2 ).
Table 2
Cox regression model for univariate analysis: OS and CSS
Abbreviations: OS overall survival, CSS cause-specific survival, CI confidence interval, HR hazard ratio
| Parameter | OS | CSS | ||||
| HR | 95%CI | P | HR | 95%CI | P | |
| Sex | ||||||
| Female | Reference | Reference | ||||
| Male | 1.262 | 1.19–1.34 | < 0.001 | 1.249 | 1.15–1.35 | < 0.001 |
| Age | ||||||
| < 60 years | Reference | Reference | ||||
| > 60 years | 3.967 | 3.67–4.29 | < 0.001 | 3.333 | 2.99–3.71 | < 0.001 |
| B symptoms | ||||||
| Absence | Reference | Reference | ||||
| Presence | 1.499 | 1.4–1.6 | < 0.001 | 1.979 | 1.81–2.16 | < 0.001 |
| Year of diagnosis | ||||||
| 2013–2017 | Reference | Reference | ||||
| 2018–2022 | 1.123 | 1.05–1.2 | < 0.001 | 0.888 | 0.81–0.97 | 0.011 |
| Race | ||||||
| Black | Reference | Reference | ||||
| White | 0.9 | 0.79–1.02 | 0.105 | 0.92 | 0.76–1.11 | 0.38 |
| Other | 0.739 | 0.62–0.88 | < 0.001 | 0.831 | 0.65–1.06 | 0.137 |
| Chemotherapy | ||||||
| No/unknown | Reference | Reference | ||||
| Yes | 1.005 | 0.95–1.06 | 0.858 | 1.288 | 1.19–1.4 | < 0.001 |
| Radiotherapy | ||||||
| No/unknown | Reference | Reference | ||||
| Yes | 0.636 | 0.58–0.7 | < 0.001 | 0.523 | 0.45–0.6 | < 0.001 |
| Ann Arbor stage | ||||||
| I/II | Reference | Reference | ||||
| III/IV | 1.344 | 1.27–1.42 | < 0.001 | 1.893 | 1.73–2.07 | < 0.001 |
| Prior cancer history | ||||||
| No | Reference | Reference | ||||
| Yes | 1.767 | 1.66–1.88 | < 0.001 | 1.419 | 1.29–1.56 | < 0.001 |
| Marital status | ||||||
| Married | Reference | Reference | ||||
| Unmarried | 1.522 | 1.44–1.61 | < 0.001 | 1.665 | 1.54–1.8 | < 0.001 |
Multivariable analysis
After adjustment for potential confounders, marital status remained independently associated with survival (Table 3 ). Compared with married patients, those unmarried had significantly worse OS (HR, 1.62; 95% CI, 1.53–1.71; P < 0.001) and CSS (HR, 1.77; 95% CI, 1.63–1.92; P < 0.001). Other independent predictors of inferior survival included male sex (OS: HR, 1.42; CSS: HR, 1.43), older age (OS: HR, 3.91; CSS: HR, 3.53), presence of B symptoms (OS: HR, 1.57; CSS: HR, 1.87), advanced stage disease (OS: HR, 1.30; CSS: HR, 1.70), and prior cancer history (OS: HR, 1.45; CSS: HR, 1.24) (all P < 0.001). Receipt of radiotherapy was associated with improved OS (HR, 0.73; 95% CI, 0.66–0.80, P < 0.001) and CSS (HR, 0.71; 95% CI, 0.61–0.82, P < 0.001). Chemotherapy was not significantly associated with survival in the multivariable model.
Table 3
Cox regression model for multivariable analysis: OS and CSS
Abbreviations: OS overall survival, CSS cause-specific survival, CI confidence interval, HR hazard ratio
| Parameter | OS | CSS | ||||
| HR | 95%CI | P | HR | 95%CI | P | |
| Sex | ||||||
| Female | Reference | Reference | ||||
| Male | 1.423 | 1.34–1.51 | < 0.001 | 1.43 | 1.32–1.55 | < 0.001 |
| Age | ||||||
| < 60 years | Reference | Reference | ||||
| > 60 years | 3.912 | 3.61–4.24 | < 0.001 | 3.531 | 3.16–3.94 | < 0.001 |
| B symptoms | ||||||
| Absence | Reference | Reference | ||||
| Presence | 1.573 | 1.47–1.68 | < 0.001 | 1.873 | 1.71–2.05 | < 0.001 |
| Year of diagnosis | ||||||
| 2013–2017 | Reference | Reference | ||||
| 2018–2022 | 1.082 | 1.01–1.16 | 0.02 | 0.866 | 0.79–0.95 | 0.002 |
| Race | ||||||
| Black | Reference | Reference | ||||
| White | 0.945 | 0.83–1.07 | 0.39 | 1.018 | 0.84–1.23 | 0.855 |
| Other | 0.884 | 0.74–1.05 | 0.163 | 1.034 | 0.81–1.32 | 0.788 |
| Chemotherapy | ||||||
| No/unknown | Reference | Reference | ||||
| Yes | 0.953 | 0.9–1.01 | 0.114 | 1.062 | 0.97–1.16 | 0.172 |
| Radiotherapy | ||||||
| No/unknown | Reference | Reference | ||||
| Yes | 0.729 | 0.66–0.8 | < 0.001 | 0.706 | 0.61–0.82 | < 0.001 |
| Ann Arbor stage | ||||||
| I/II | Reference | Reference | ||||
| III/IV | 1.304 | 1.22–1.39 | < 0.001 | 1.697 | 1.54–1.87 | < 0.001 |
| Prior cancer history | ||||||
| No | Reference | Reference | ||||
| Yes | 1.448 | 1.36–1.54 | < 0.001 | 1.237 | 1.12–1.36 | < 0.001 |
| Marital status | ||||||
| Married | Reference | Reference | ||||
| Unmarried | 1.618 | 1.53–1.71 | < 0.001 | 1.767 | 1.63–1.92 | < 0.001 |
Discussion
In this population-based study using SEER data from 2013 to 2022, we demonstrated that marital status was significantly associated with survival outcomes in FL patients. Unmarried patients exhibited inferior OS and CSS compared with their married counterparts, even after adjustment for key clinical and demographic factors. To our knowledge, this is the first study to specifically investigate the prognostic relevance of marital status in FL.
In hematologic malignancies, including mantle cell lymphoma and multiple myeloma, similar survival advantages associated with marriage have been reported [ 7 , 12 ]. Our findings suggest that marital status may be particularly impactful in a disease like FL, which requires long-term follow-up and close monitoring to detect disease progression or transformation. In this cohort of over 23,000 patients, unmarried individuals were more likely to be female, older, and Black, characteristics previously associated with socioeconomic vulnerability and healthcare disparities. Although B symptoms were more frequent among unmarried patients, this factor was adjusted for in both the multivariable models and the matched cohort; nonetheless, delayed diagnosis or reduced healthcare engagement among unmarried individuals may contribute to a more symptomatic presentation. While the pathophysiological mechanisms underlying this association remain complex, several explanations have been proposed. Spousal support may promote earlier health-seeking behavior, facilitate timely diagnosis, and encourage adherence to therapy [ 13 ]. Moreover, marriage has been associated with improved psychological resilience and lower rates of depression, as well as better adherence to long-term surveillance, timely medical follow-up, and sustained engagement in chronic disease management. These factors are particularly important for patients with indolent cancers such as FL, where continuous monitoring and periodic treatment over many years are essential for optimal outcomes [ 14 , 15 ].
Although radiotherapy appeared to be associated with improved survival in both univariate and multivariable analyses, this finding likely reflects underlying differences in disease presentation rather than a direct therapeutic effect. In clinical practice, radiotherapy is predominantly used for patients with limited-stage or low-tumor-burden FL, who inherently have more favorable prognoses [ 16 , 17 ]. Similarly, patients who did not receive chemotherapy represent a heterogeneous group, including those managed with observation for low-burden disease, those treated with radiotherapy alone, and those receiving chemo-free targeted approaches. These treatment strategies are generally reserved for patients with favorable disease biology, which inherently confers an excellent prognosis independent of cytotoxic therapy [ 18 , 19 ]. Prior cancer history was also adjusted for as a covariate, as it may influence baseline health status and long-term survival. By including these variables in both multivariable and propensity score matched analyses, we aimed to minimize confounding related to treatment selection and comorbidity while preserving the representativeness of the real-world FL population captured in SEER.
Commonly used prognostic models in FL, including FLIPI, FLIPI-2, and PRIMA-PI, rely largely on clinical indicators of tumor burden and patient status [ 4 ]. Emerging evidence supports the prognostic value of molecular markers [ 20 – 22 ], but these biomarkers remain costly and not routinely accessible. Marital status represents a simple and readily obtainable indicator of social support that may complement established clinical and molecular prognostic markers. Incorporating marital status as an adjunct to conventional risk stratification may help identify patients who could benefit from additional supportive care interventions. Similar efforts have demonstrated survival and quality-of-life benefits in other cancer populations [ 23 – 25 ]. Further prospective studies are warranted to determine whether structured social support can mitigate the risks associated with unmarried status in FL.
This study has several limitations. First, marital status is recorded only at diagnosis and cannot be analyzed as a time-varying factor, potentially missing changes during follow-up. Second, SEER marital status is limited to legally defined categories and does not capture unregistered long-term partnerships or the nuances of patients’ actual social support networks. Individuals classified as ‘never married’ may still have substantial partner support, which could not be accounted for in this analysis. Third, socioeconomic factors such as income, education level, and insurance coverage, which are not captured in the SEER dataset, may influence access to care and treatment adherence, and therefore remain important unmeasured confounders in this analysis. Additionally, prognostic markers such as POD24, end-of-treatment response, FLIPI score, and detailed treatment information were not available within the SEER dataset. Because these variables reflect disease biology and treatment course, their absence limits our ability to examine how marital status may interact with biologic risk or influence treatment patterns. Future studies incorporating comprehensive response assessments and therapeutic data will be essential to address these important questions. Moreover, due to the relatively short follow-up time for patients diagnosed in the modern treatment era, long-term outcomes such as 10-year or 20-year survival could not be reliably evaluated. As a result, the prognostic impact of marital status beyond the 5-year timeframe remains to be clarified in future studies with extended longitudinal follow-up. Nonetheless, the large sample size and comprehensive follow-up of the SEER database provide meaningful insights into the prognostic impact of marital status in FL.
In conclusion, unmarried patients with follicular lymphoma showed significantly worse 5-year survival outcomes compared with married patients, independent of clinical factors. These findings highlight the prognostic relevance of marital status and underscore the need for supportive strategies tailored to unmarried individuals who may be at increased risk for inferior outcomes.
Acknowledgements
The authors thank the SEER database for the availability of the data.
Author contributions
Xudong Li and Xiaojie Fang designed the study. Songyuan He, Hao Song, Weiyi Zuo, and Shu Liu contributed to data collecting and analysis. Songyuan He and Xudong Li wrote the initial draft of the manuscript. All authors read and approved the manuscript.
Funding
This work is supported by National Natural Science Foundation of China (82204532 to Shu Liu), and Science and Technology Program of Guangzhou (2023A04J1794 to Shu Liu).
Data availability
Data are available in a public, open-access repository. Specifically, the data used in this study were obtained from the SEER Research Data, which is publicly accessible at [https://seer.cancer.gov/data/.](https:/seer.cancer.gov/data).
Declarations
Ethics approval
All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Xiaojie Fang, Email: fangxj@sysucc.org.cn.
Xudong Li, Email: 495820417@qq.com.
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Associated Data
Data Availability Statement
Data are available in a public, open-access repository. Specifically, the data used in this study were obtained from the SEER Research Data, which is publicly accessible at [https://seer.cancer.gov/data/.](https:/seer.cancer.gov/data).