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Original article
Cardiology care, cardiovascular comorbidities and all-cause mortality in long-term breast cancer survivors: a retrospective cohort study

Atención cardiológica, comorbilidades cardiovasculares y mortalidad por todas las causas en supervivientes a largo plazo de cáncer de mama: un estudio de cohorte retrospectivo

Marina Botello-MarabottoaMercè ComasabDavid Abbad-GómezabLaia DomingoabBerta Ibáñez-BeroizbcIbai TamayobcBeatriz Poblador-PloubdAntonio Gimeno-MiguelbdMáximo RedondobeMaría PadillabeIsabel del CurabfTeresa SanzbfAntonio Díaz-HolgadofHelena Tizón-MarcosghiXavier CastellsabMaría Salaab
https://doi.org/10.1016/j.rec.2026.06.003
La versión en español de este artículo estará disponible en breve
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10.1016/j.rec.2026.06.003
Abstract
Introduction and objectives

Breast cancer survivors (BCS) have an elevated risk of cardiovascular disease (CVD), but standardized follow-up protocols remain limited. We aimed to describe cardiovascular comorbidities and the utilization of specialized health services, particularly cardiology services, among BCS, and to examine their association with mortality.

Methods

We conducted a retrospective cohort study of 6186 BCS diagnosed between 2000 and 2006 who survived at least 5 years after diagnosis. Participants were followed up from 2012 to 2016. Health care use and comorbidities obtained from electronic health records were analyzed. A multivariate time-dependent Cox proportional hazards model was used to assess the association between use of cardiology services and all-cause mortality.

Results

A total of 43.6% of long-term BCS had CVD at the beginning of follow-up. Women with CVD were older (mean age 71.8 vs 62 years; P<.001) and had a substantially higher comorbidity burden than those without CVD (5.83 vs 1.96; P <.001). During follow-up, 781 BCS (12.6%) died. Nonsurvivors were older and had a greater and more severe baseline comorbidity burden than survivors. They also had higher rates of specialist visits. Use of cardiology services was associated with lower mortality, although the association did not reach statistical significance (HR, 0.84; 95%CI, 0.67-1.05; P=.12).

Conclusions

The prevalence of CVD among BCS was high, although only 18.8% used cardiology services. Nonsurvivors had a higher CVD burden and severity, and showed greater use of health care services.

Keywords

Breast neoplasm
Cancer survivors
Cardiovascular diseases
Longitudinal study
Health care services

Abbreviations

BCS
CVD
INTRODUCTION

Breast cancer is the most common cancer among women worldwide, with more than 2.3 million new cases reported in 2022.1 Advances in early detection and treatment have substantially improved survival, resulting in a large and diverse population of breast cancer survivors (BCS) who face unique long-term physical, psychological, and social challenges.2 As survivorship continues to increase, care now extends beyond cancer treatment to focus on health maintenance, quality of life, and the management of late treatment-related effects.

Cardiovascular disease (CVD) has emerged as a major concern in this population. Certain cancer therapies, such as anthracyclines, HER2-targeted agents, radiation, and hormonal treatments, can cause acute or chronic cardiotoxicity, leading to left ventricular dysfunction, heart failure, or ischemic heart disease.3 The risk of cardiovascular mortality is also elevated among BCS and may not become apparent until 7 years after diagnosis.4 However, substantial gaps remain in the characterization of long-term cardiovascular risk in cancer survivors.5 These gaps highlight the need for structured surveillance strategies. Annual clinical cardiovascular risk assessments are recommended for all adult cancer survivors to optimize the management of cardiovascular risk factors, promote healthy lifestyles, and monitor symptoms.6 However, the implementation of such protocols remains limited and inconsistent7,8 and BCS are often not properly informed of their cardiovascular risk.9

Only a limited number of studies have directly assessed health care service utilization by BCS.10,11 While several studies have highlighted the need to develop cardio-oncology services for a more tailored follow-up of BCS,12,13 the actual use of cardiology services by BCS remains relatively unexplored, as most published studies are cross-sectional or have small sample sizes.7,14

Understanding patterns of health care utilization among BCS is essential to identify care gaps and improve follow-up strategies. Therefore, we aimed to describe cardiovascular comorbidities and specialized health services use, especially cardiology services, among BCS, and to examine their association with mortality.

METHODSStudy design and population

This study was conducted using data from the longitudinal SURvival Breast CANcer (SURBCAN) cohort, developed within the framework of the Red de Investigación en Cronicidad, Atención Primaria y Promoción y Prevención de la Salud (RICAPPS; Network for Research on Chronicity, Primary Care, and Health Promotion and Prevention).15 For the purposes of the present study, we focused specifically on the long-term BCS subgroup from the SURBCAN cohort. SURBCAN is a population-based, retrospective cohort including long-term BCS diagnosed between 2000 and 2006 who had survived at least 5 years postdiagnosis, and age- and primary care area-matched women without breast cancer. The cohort included BCS from 5 Spanish regions: Catalonia (n=838), Andalusia (n=99), the Community of Madrid (n=1087), the Chartered Community of Navarre (n=1756), and Aragon (n=2406). All personal data were anonymized, and no written informed consent was necessary for our study. The study was performed in accordance with the Declaration of Helsinki of the World Medical Association and was approved by the Parc de Salut Mar Research Ethics Committee (CEIM PSMAR 2019/8639/I).

Data source

Information was obtained from the electronic health records of the Spanish National Health System of the participating regions for the study period (2012-2016). Extracted data included information on primary, specialty, and hospital care (emergency visits, admissions, and diagnostic procedures), as well as sociodemographic and lifestyle variables (age, nationality, health coverage, smoking, and alcohol use), prescription data, and comorbidities. For BCS, breast cancer-specific information was also retrieved.

Disease classification and comorbidity definitions

Diagnoses were coded according to the International Classification of Diseases, 9th and 10th Revisions (ICD-9 and ICD-10), depending on the regional system, and were extracted from electronic health records at the beginning and end of follow-up. Only chronic conditions, as defined by the Agency for Healthcare Research and Quality's Clinical Classification Software Refined (CCS/CCSR v.2019),16 were included in the comorbidity analysis. CVDs were defined by ICD-9 codes 390-459 and ICD-10 codes 100-199. The 5 most prevalent CVDs (hypertensive disease, arrhythmia, cerebrovascular disease, heart failure, and ischemic heart disease) were analyzed. Comorbidities were assessed at baseline and at the end of follow-up. Vital status was determined from mortality or insurance records, depending on availability.

Descriptive statistics

Baseline characteristics, comorbidities, and specialist visit rates (per person-year) were summarized by CVD at baseline, and vital status was summarized at the end of follow-up. Comorbidities were assessed at baseline (at cohort entry, which included all comorbidities present at that time) and were tracked throughout the follow-up period, with the date of each new diagnosis recorded as it occurred. For descriptive analyses, comorbidities were summarized at baseline and at the end of follow-up. The subgroup of BCS with CVD at baseline was further described by vital status at the end of follow-up and cardiology service use. Group comparisons were performed using either the t-test or the Wilcoxon rank-sum test, as appropriate. Rates between groups were compared using the Poisson rate comparison test. All analyses were conducted using R software (version 4.3.0).

Event-centered cardiology use

Patterns of cardiology service use were analyzed relative to death or the end of follow-up. Follow-up time was aligned to the event of interest (death for nonsurvivors and end of follow-up for survivors), defined as time 0, and divided into consecutive 6-month intervals counted retrospectively to cohort entry. Cardiology visits were assigned to intervals based on their timing relative to the event, and person-time was calculated including only women who remained under follow-up during each interval. Cardiology visit rates were then calculated and plotted by aggregating visits and person-time per interval among participants.

Multivariate analysis

The association between specialist visits and all-cause mortality was examined using Cox proportional hazards models with time-dependent covariates. Follow-up time was defined from the date of study entry (January 1, 2012) until the date of death or the end of follow-up (December 31, 2016), whichever occurred first. Covariates included age at baseline and the number of distinct CVDs and other comorbidities at baseline. Cardiology visits were modeled as a time-dependent binary variable, coded 0 until the patient attended their first visit, and 1 thereafter. Acquired comorbidities and specialist visits (to family physicians, oncologists, and radiologists), used as proxies for clinical severity and health care utilization, were included as time-dependent variables using cumulative counts. Follow-up was structured in a counting process (start-stop) format, with participants contributing multiple intervals updated at each new comorbidity or specialist visit, incrementing cumulative counts over time.

The proportional hazards assumption was verified for baseline covariates using Schoenfeld residuals and residual plots, with no violations detected. Hazard ratios for time-dependent covariates represent average effects over the follow-up period.

Adjusted survival curves were derived from the time-dependent Cox model under 2 hypothetical scenarios: a) no cardiology service use during follow-up, and b) cardiology service use from baseline onward. Baseline covariates were fixed at their mean or reference values, and time-dependent covariates were set to their baseline values throughout follow-up. All analyses were performed using R software (version 4.3.0) and the survival package.

RESULTSBaseline characteristics and comorbidities

A total of 6186 BCS were included in the analysis, of whom 2710 (43.8%) had CVD at baseline. Women with CVD were older (mean age 71.8 years vs 62 years; P <.001), and had a higher comorbidity burden compared with those without CVD (5.83 vs 1.96; P <.001). During follow-up, women with baseline CVD also had a higher mean number of acquired comorbidities and CVD events, as well as higher rates of both outcomes (table 1). During follow-up, 781 BCS (12.6%) died. Mortality was slightly higher among women with baseline CVD compared with those without (13.5% vs 11.9%), although this difference was not statistically significant (P=.06). Nonsurvivors were significantly older at baseline than survivors at the end of follow-up (mean age 77.2 years vs 64.7 years; P <.001). Nonsurvivors also had a higher mean number of baseline comorbidities (4.6 vs 3.5; P=.55) and acquired more new comorbidities during follow-up (0.7 vs 0.6; P <.001), corresponding to higher incidence rates (0.28 vs 0.14 per person-year; P <.001). Although the mean number of acquired cardiovascular comorbidities was slightly higher among nonsurvivors (0.21 vs 0.13; P=.52), the incidence rate of acquired CVD was significantly higher in this group (0.08 vs 0.03 per person-year; P <.001) (table 2).

Table 1.

Comorbidities, health care use and mortality among BCS according to CVD at baseline (n=6186)

Variable  TotalN=6186  Baseline CVDn=2710 (43.8%)  No baseline CVDn=3476 (56.2%)  P 
Age  66.22 (12.6)  71.77 (10.8)  61.96 (12.2)  <.001 
Baseline comorbidities
Baseline comorbidities  3.66±3.8  5.83±4.3  1.96±2.2  <.001 
Baseline CVD  0.70±1.2  1.59±1.35 
Acquired comorbidities
Acquired comorbidities  0.64±1.4  0.82±1.7  0.51±1.04  <.001 
Acquired comorbidities, rate (95%CI)  0.15 (0.14-0.15)  0.19 (0.8-0.2)  0.11 (0.11-0.12)  <.001 
Acquired CVD  0.14±0.5  0.19±0.7  0.10±0.4  <.001 
Acquired CVD, rate (95%CI)  0.03 (0.03-0.04)  0.04 (0.04-0.05)  0.02 (0.02-0.03)  <.001 
Specialist care
Rate of specialist visits (95%CI)  20.79 (20.7-20.8)  23.92 (23.8-24.0)  18.31 (18.2-18.4)  <.001 
Distinct specialists visited  7.39±3.9  7.6±4.0  7.2±3.8  <.001 
Use of cardiology services
Use of cardiology services  1163 (18.8)  573 (21.1)  590 (17)  <.001 
Rate of cardiology visits (95%CI)  0.18 (0.17-0.18)  0.2 (0.19-0.2)  0.16 (0.15-0.16)  <.001 
Mortality  781 (12.6%)  367 (13.5%)  414 (11.9%)  .06 

95%CI, 95% confidence interval; CVD, cardiovascular disease.

The data are expressed as No. (%) or mean±standard deviation.

Table 2.

Comorbidity (total and CVD) and health care use among patients with breast cancer according to vital status at the end of follow up (n=6186)

Variable  Nonsurvivorsn=781 (12.6%)  Survivorsn=5405 (87.4%)  P 
Age  77.17±13.3  64.65±11.6  <.001 
Baseline comorbidities
Baseline comorbidities  4.56±5.6  3.53±3.5  .55 
Baseline CVD  1.16±2.02  0.63±<.001 
Acquired comorbidities
Acquired comorbidities  0.72±2.1  0.63±1.2  <.001 
Acquired comorbidities, rate (95%CI)  0.28 (0.26-0.30)  0.14 (0.13- 0.14)  <.001 
Acquired CVD  0.21±0.8  0.13±0.5  .52 
Acquired CVD,Rate (95%CI)  0.08 (0.07-0.09)  0.03 (0.03-0.03)  <.001 
Specialist care
Rate of specialist visits (95%CI)  33.50 (33.3-33.8)  19.75 (19.7-19.8)  <.001 
Distinct specialists visited  6.25±4.0  7.56±3.8  <.001 
Use of cardiology services
Use of cardiology services  149 (19.1)  1014 (18.8)  .87 
Rate of cardiology visits (95%CI)  0.29 (0.27-0.31)  0.17 (0.16-0.17)  <.001 

95%CI, 95% confidence interval; CVD, cardiovascular disease.

The data are expressed as No. (%) or mean±standard deviation.

Health care utilization patterns

BCS with baseline CVD had a higher rate of specialist visits (23.9 vs 18.3) and consulted a greater number of specialist services than women without baseline CVD (7.6 vs 7.2) (table 1). When stratified by vital status (table 2), nonsurvivors had a higher rate of specialist visits than survivors (33.5 vs 19.8; P <.001) but consulted fewer distinct specialists (mean, 6.3 vs 7.6; P <.001). Family physicians accounted for the highest visit rate in both groups, followed by oncology and radiology services (figure 1). The largest differences between groups were observed for oncology and radiology visits, which were more frequent among nonsurvivors, whereas survivors had relatively higher rates of ophthalmology and gynecology visits.

Figure 1.

Visit rates per person-year by specialty among survivors and nonsurvivors. Attendance rates are shown for nonsurvivors (blue) and survivors (red) across specialty services. For visualization purposes, visits to family physicians were omitted from the graph; the mean number of visits to family physicians was 16.25 for nonsurvivors and 10.1 for survivors.

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Cardiology service use

Overall, only 21% of women with baseline CVD used cardiology services compared with 17% of BCS without baseline CVD (table 1). When stratified by vital status (table 2), 19.1% of nonsurvivors and 18.8% of survivors visited a cardiologist at least once during follow-up (P=.87). However, nonsurvivors had a higher rate of cardiology visits than survivors (0.3 vs 0.2 per person-year; P <.001). Event-centered analyses of cardiology use prior to death (nonsurvivor group) and at the end of follow-up (survivors) revealed distinct temporal patterns (figure 2). Cardiology use was higher among nonsurvivors at all time points, with a peak approximately 1 year before death, whereas survivors showed a gradual decline in cardiology visits over time.

Figure 2.

Event-centered patterns of cardiology service use among breast cancer survivors. The figure illustrates event-centered trajectories of cardiology attendance rates (visits per person-year) according to death (nonsurvivors) or end of follow-up (survivors). Lines represent rates per person-year, and shaded areas indicate 95% confidence intervals.

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Cardiovascular comorbidities

When the prevalence of specific CVD at baseline was examined (table 3), the most frequent CVD in both groups was hypertensive disease (35.7% in nonsurvivors and 35.5% in survivors; P=.94). In contrast, arrhythmia (10.6% vs 4.2%), cerebrovascular disease (12.6% vs 4.0%), heart failure (8.5% vs 2.2%), and ischemic heart disease (3.7% vs 1.8%) were more prevalent in nonsurvivors (all P <.001). Among newly acquired CVD, only ischemic heart disease differed significantly between groups, with a higher incidence in nonsurvivors (1.8% vs 0.6%; P <.001).

Table 3.

Prevalence of specific CVD and incidence of CVD acquired during follow-up

Condition  Total  Nonsurvivors  Survivors  P 
Baseline CVD
Any baseline CVD  2710 (43.9)  367 (46.7)  2343 (43.4)  <.001 
Hypertensive disease  2271 (36.7)  279 (35.7)  1919 (35.5)  .94 
Arrhythmia  323 (5.2)  83 (10.6)  228 (4.2)  <.001 
Cerebrovascular disease  321 (5.2)  98 (12.6)  214 (4.0)  <.001 
Heart failure  191 (3.1)  66 (8.5)  118 (2.2)  <.001 
Ischemic heart disease  140 (2.3)  29 (3.7)  99 (1.8)  <.001 
Acquired CVD during follow-up
Any acquired CVD  621 (10.0)  82 (10.5)  539 (10.0)  .52 
Hypertensive disease  272 (4.4)  25 (3.2)  228 (4.2)  .21 
Arrhythmia  141 (2.3)  19 (2.4)  112 (2.1)  .60 
Cerebrovascular disease  124 (2.0)  17 (2.2)  99 (1.8)  .60 
Heart failure  100 (1.6)  18 (2.3)  80 (1.5)  .12 
Ischemic heart disease  50 (0.8)  14 (1.8)  30 (0.6)  <.001 

CVD, cardiovascular disease.

The data are expressed as No. (%).

Use of cardiology services and mortality in BCS with baseline CVD

The characteristics of BCS with CVD at baseline according to cardiology service use and vital status at the end of follow-up are shown in table 4. Among these women, those who used cardiology services had a lower proportion of deaths than those who did not (10.3% vs 14.4%; P=.013). However, women who attended cardiology services also showed a higher incidence of new CVD events during follow-up (21.6% vs 9.1%; P=.002). BCS who used cardiology services had a higher rate of specialist visits overall (31.2 vs 22.0; P <.001) and consulted a broader range of specialists compared with those who did not (10.9 vs 6.8; P <.001), irrespective of vital status at the end of follow-up.

Table 4.

Characteristics of breast cancer survivors with baseline CVD according to cardiology service use and vital status (n=2710)

Characteristics  Use of cardiologyNo use of cardiologyP* 
  Total  Nonsurvivors  Survivors  Total  Nonsurvivors  Survivors   
No. (%)  573 (21.1)  59 (10.3)  514 (89.7)  2137 (78.9)  308 (14.4)  1829 (85.6)   
Age  71.40±10.6  77.79±9.6  70.84±10.5  71.86±10.8  80.61±10.3  70.48±10.2  .41 
Comorbidity burden
Baseline comorbidities  5.53±3.2  7.34±3.6  5.33±3.1  5.91±4.6  8.80±5.8  5.43±4.2  .53 
Acquired comorbidities  1.12±1.6  0.83±1.2  1.16±1.7  0.74±1.7  1.27±2.9  0.66±1.4  <.001 
Cardiovascular comorbidities
Women with acquired CVD  124 (21.6)  14 (23.7)  110 (21.4)  194 (9.1)  51 (16.6)  143 (7.8)  .002 
Baseline CVD  1.65±1.1  2.39±1.4  1.56±1.0  1.58±1.4  2.48±2.5  1.43±1.1  <.001 
Acquired CVD  0.31±0.8  0.34±0.7  0.31±0.8  0.16±0.7  0.39±1.2  0.12±0.5  <.001 
Health care utilization
Rate of specialist visits, (95%CI)  31.19 (31.0-31.4)  42.71 (41.8- 43.7)  30.30 (30.1-30.5)  21.97 (21.9-22.1)  27.82 (27.5-28.2)  21.34 (21.2-21.4)  <.001 
Distinct specialists visited  10.85±3.7  10.86±4.6  10.85±3.6  6.78±3.6  5.53±3.7  6.99±3.6  <.001 

95%CI, 95% confidence interval; CVD, cardiovascular disease.

The data are expressed as No. (%) or mean±standard deviation.

*

P value calculated for totals (use vs no use of cardiology services).

Multivariate analysis

In the fully adjusted Cox model (figure 3), use of cardiology services was associated with lower all-cause mortality, although the association did not reach statistical significance (hazard ratio [HR], 0.84; 95% confidence interval [95% CI], 0.67-1.05; P=.12). This estimate was obtained after adjustment for comorbidity burden and health care utilization patterns. Additional baseline comorbidities, other than CVD, were associated with a lower mortality risk (HR, 0.94; 95%CI, 0.92-0.97; P <.001). In contrast, noncardiovascular comorbidities acquired during follow-up were associated with higher mortality (HR, 1.10; 95%CI, 1.02-1.19; P=.02). Neither baseline nor acquired CVD were associated with all-cause mortality.

Figure 3.

Multivariable Cox model evaluating associations between comorbidity, health care use, and mortality risk. The left-hand panel lists all covariates included in the model with their hazard ratios (HR), 95% confidence intervals (95%CI), and P-values. The right-hand panel presents the corresponding forest plot. CVD, cardiovascular disease; FP, family physician.

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Among time-dependent utilization proxies of clinical severity, cumulative visits to family physician (HR, 1.01), oncology (HR, 1.02), and radiotherapy services (HR, 1.07) were independently associated with slightly higher mortality (all P <.001). Age was also associated with mortality (HR, 1.09; 95%CI, 1.08–1.10; P <.001).

DISCUSSION

We analyzed a large, retrospective Spanish cohort of long-term BCS, focusing on cardiovascular comorbidities and health care services utilization, especially the use of cardiology services, and their association with mortality (figure 4). This setting reflects a phase of survivorship characterized by aging and greater acquired comorbidity, and the findings should be interpreted within this specific context.

Figure 4.

Central illustration. Cardiovascular comorbidity, cardiology care, and mortality among long-term breast cancer survivors. Retrospective cohort of 6186 Spanish breast cancer survivors (diagnosed 2000-2006; ≥ 5-year survival) followed up from 2012 to 2016. Panel 1: cohort overview. Panel 2: nonsurvivors (12.6%) were older, had higher comorbidity, more severe cardiovascular disease, and more intense health care use. Panel 3: Covariate-adjusted survival probabilities derived from the time-dependent Cox model. These curves should be interpreted as model-based standardized survival functions under fixed exposure regimes, rather than observed survival trajectories. aHR, adjusted hazard ratio; BCS, breast cancer survivors.

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The prevalence of CVD in our BCS cohort (43%), which included only women surviving at least 5 years after diagnosis, was higher than that in studies including 1-year survivors,17 likely reflecting older age and longer follow-up. However, it was lower than hypertension rates reported at diagnosis in other cohorts.18 These differences may reflect varying follow-up durations, measurement timing, and survivor bias, as early events or more severe disease may be underrepresented in long-term survivors.19 Furthermore, women with baseline CVD were older and had a higher comorbidity burden than those without baseline CVD, suggesting that CVD in this population occurs within a broader context of multimorbidity, likely influenced by older age.20

Although the overall health care use among BCS has been described previously,10 evidence is scarce on specialist or cardiology utilization and its impact on outcomes.14 We extend these findings by characterizing longitudinal patterns of specialist care.

Nonsurvivors showed more intensive health care use but consulted fewer distinct specialists, consistent with evidence of increasing service concentration near the end of life, regardless of the cause of death.21 In particular, the concentration of visits in cancer management-related services may reflect cancer recurrence and a cancer-related cause of death. These patterns are consistent with time-dependent health care utilization as measures capturing underlying disease severity, which explains their positive association with mortality in adjusted analyses. Furthermore, these patterns and are in line with prior studies reporting greater end-of-life healthcare use among individuals dying of cancer.22,23

Many BCS, including those with baseline CVD, and particularly those who died during follow-up, did not access cardiology services. Importantly, cardiovascular care in this population is not exclusively delivered by cardiologists and may be provided by primary care or other specialties. Nevertheless, this mismatch between need and specialized care delivery may arise from limitations in the referral system or patient-related barriers.24,25 Notably, the subgroup of nonsurvivors who had CVD and did not use cardiology services had the highest mean age and the greatest comorbidity burden at baseline. These patients also consulted the lowest number of different specialists. This finding highlights the need for tailored strategies to ensure adequate cardiology follow-up, especially in BCS with a higher CVD comorbidity burden, as seen here and in earlier studies,26 and who might face additional barriers such as frailty, mobility limitations, or competing health priorities.27 Previous studies have reported less intensive health care use at the end of life among older patients compared with younger nonsurvivors, regardless of the cause of death.21 There have also been reports of the increased challenges encountered by older adults, especially women, in accessing health care, influenced by health, socioeconomic, and contextual factors.28

Several studies have reported higher cardiovascular mortality among BCS.29,30 In our study, although cause of death was not available, crude mortality was slightly higher among survivors with baseline CVD, and nonsurvivors had a higher prevalence of CVD, particularly severe conditions such as arrhythmia, cerebrovascular disease, heart failure, and ischemic heart disease.30–32

Among women with baseline CVD, cardiology utilization was associated with lower mortality. After adjustment for age, baseline and the cumulative number of comorbidities, and health care use intensity, cardiology use remained associated with a lower hazard of all-cause mortality, although this association did not reach statistical significance. These findings are consistent with current onco-cardiology recommendations emphasizing structured, risk-adapted cardiovascular follow-up and clinically indicated cardiology referral in long-term cancer survivors.6

Differences in cardiology services use over time between survivors and nonsurvivors at the end of follow-up were observed. Nonsurvivors consistently showed more intense cardiology use throughout follow-up, without a decline near the end of life. Conversely, the reduced cardiology use observed among survivors toward the end of follow-up may reflect a general decline in long-term surveillance among those with fewer comorbidities, as previously reported,33 potentially reflecting a natural tendency to disengage from care as the perceived health threat diminishes. The inverse association with comorbidity burden may reflect more medical visits and closer follow-up, which may explain the apparent protective effect of higher baseline comorbidities.

The main strengths of this study include its large, population-based national cohort with real-world health care data, enabling detailed assessment of health care use among BCS. Its longitudinal design allowed the evaluation of long-term patterns and outcomes across specialties, highlighting gaps in cardiology care and opportunities for integrated cardio-oncology management. Modeling cardiology use and the cumulative number of comorbidities as time-dependent covariates provides a more accurate representation of patients’ evolving clinical status, although it may reduce statistical power. As with any study using administrative health care data, our analysis may be affected by incomplete or inaccurate visit codes and dates, as well as missing or outdated patient information. Cause of death data were unavailable, limiting the ability to directly link outcomes to cardiovascular or cancer-related events. Accordingly, findings should be interpreted in terms of all-cause mortality only. Data on molecular cancer type and treatments were not available, preventing assessment of treatment effects on cardiology follow-up and outcomes, as well as treatment-related heterogeneity. Furthermore, other unmeasured factors related to disease severity or health care-seeking behaviors may have influenced the observed associations. In particular, patients referred to cardiology are likely to differ systematically from those who are not, as referral decisions are influenced by the physician's assessment of cardiovascular risk and clinical need, which can only be partially addressed by our adjustment strategy. Finally, the follow-up extended only until 2016, when cardio-oncology practices in Spain were still emerging and were not widely implemented, which should be considered when extrapolating these findings to current clinical practice.34

CONCLUSIONS

The prevalence of CVD among BCS was high, although only 18.8% used cardiology services. Comorbidity, overall health care utilization, and cardiology service use in particular were higher in women with baseline CVD. Nonsurvivors had a higher baseline CVD burden, more severe cardiovascular conditions, and made greater use of health care services. The use of cardiology services was not statistically significantly associated with lower mortality.

FUNDING

This work was supported by PI22/00020 and PI19/00056 funded by the Instituto de Salud Carlos III (ISCIII) and cofunded by the European Union; and RD24/0005/0002, and RD21/0016/0020 funded by Instituto de Salud Carlos III (ISCIII), and by the European Union NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (MRR).

ETHICAL CONSIDERATIONS

The study was performed in accordance with the Declaration of Helsinki of the World Medical Association and approved by the Parc de Salut Mar Research Ethics Committee (CEIM PSMAR 2019/8639/I). This was a retrospective study using anonymized data; therefore, the need for written informed consent was waived by the Ethics Committee. The SAGER guidelines were not applicable to this study, as the population exclusively consisted of women and no sex/gender comparisons were performed.

STATEMENT ON THE USE OF ARTIFICIAL INTELLIGENCE

During the preparation of this work, the authors used ChatGPT for minor language refinement in limited portions of the text. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

AUTHORS’ CONTRIBUTIONS

M. Botello-Marabotto performed data analysis and drafted the manuscript. M. Comas helped with the relevant statistical tests and with interpreting the results. D. Abbad-Gómez, L. Domingo, B. Ibañez-Beroiz, I. Tamayo, B. Poblador-Plou, A. Gimeno-Miguel, M. Redondo, M. Padilla, I. del Cura, T. Sanz, A. Díaz-Holgado, H. Tizón-Marcos, and X. Castells revised the manuscript and provided feedback on epidemiological and statistical issues. M. Sala supervised the work, helped with interpreting the results, and revised and approved the final manuscript.

CONFLICTS OF INTEREST

H. Tizón-Marcos reports a public institutional leadership role as Director of the Pla Director de Malalties Cardiovasculars (Generalitat de Catalunya), outside the submitted work. The remaining authors declare no conflicts of interest.

WHAT IS KNOWN ABOUT THE TOPIC?

  • BCS are a growing population with complex, long-term health care needs.

  • BCS have an increased risk of CVD compared with the general population.

  • Standardized cardiovascular follow-up protocols for BCS are limited.

  • Actual use of health care services by long-term BCS remains poorly studied.

WHAT DOES THIS STUDY ADD?

  • The study provides a detailed characterization of cardiovascular comorbidity and CVD patterns among long-term BCS.

  • It also describes longitudinal patterns of health care utilization, especially the use of cardiology services, highlighting heterogeneous use according to comorbidity and vital status at the end of follow-up.

  • Gaps in cardiology follow-up were identified, particularly among older long-term BCS with a high comorbidity burden.

Acknowledgements

The authors acknowledge the dedication and support of the SURBCAN Study Group (alphabetical order): IMIM (Hospital del Mar Medical Research Institute), Barcelona; Costa del Sol Hospital, University of Malaga: Grupo EpiChron de Investigación en Enfermedades Crónicas del Instituto Aragonés de Ciencias de la Salud, Zaragoza; Primary Care Research Unit, Primary Care Management, 12 de Octubre University Hospital, Madrid; Grupo de Investigación en Servicios Sanitarios y Cronicidad de la Fundación Miguel Servet, Navarre.

APPENDIX
PRINCIPAL INVESTIGATORS AND PARTICIPATING CENTERS

The authors guarantee that the following researchers are responsible for the data published in this study:

Hospital del Mar Research Institute (Barcelona, Spain): María Sala; Navarrabiomed-UPNA (Pamplona, Spain): Berta Ibáñez-Beroiz; Instituto Aragonés de Ciencias de la Salud (Zaragoza, Spain): Antonio Gimeno-Miguel; Hospital Costa del Sol (Malaga, Spain): Máximo Redondo; Hospital 12 de Octubre (Madrid, Spain): Isabel del Cura.

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