Changes in leukocyte telomere length following comprehensive cardio-oncology rehabilitation in breast cancer survivors: A pilot randomized prospective study

INTRODUCTION

Cardiovascular disease (CVD) is currently the leading cause of death among breast cancer survivors, with their risk of CVD exceeding that of the general population [1][2]. In addition to shared risk factors for both malignancies and CVD (such as smoking, an unhealthy diet, obesity, and physical inactivity), a major contributor is the cardiotoxicity of widely used breast cancer treatments, including chemotherapy and targeted, radiation, and hormone therapies [1].

Cardio-oncology rehabilitation (COR) aims to improve cardiorespiratory fitness, manage conventional CVD risk factors, enhance psychosocial well-being, and increase health literacy. It represents a promising strategy to reduce cardiovascular morbidity and mortality in cancer survivors, including those with breast cancer¹ [3][4]. The efficacy of such cardiac rehabilitation programs is evaluated using outcomes with proven prognostic value, including the management of modifiable CVD risk factors. Among these, cardiorespiratory fitness¹ serves as the primary marker of physical performance and the gold standard for its assessment [5][6].

Telomere length – the terminal chromosomal regions that preserve genomic integrity during cell division – is a genetic marker of overall health and is associated with cardiovascular risk [7][8]. Telomeres reflect the biological age of cells and the extent of their damage [9], which is particularly relevant for cancer patients in whom toxic anticancer treatment exacerbates cellular senescence [10][11]. Current evidence suggests that physical activity involving regular moderate- and vigorous-intensity aerobic training, a key component of cardiac rehabilitation programs, helps maintain telomere length [12]. Beyond physical exercise, other lifestyle factors, such as diet, body mass index (BMI), and psychological well-being, can also affect telomere length, serving as targets for intervention during the rehabilitation process [13]. Given the significance of telomere length as a cardiovascular risk marker, using this metric to evaluate the efficacy of cardiac rehabilitation programs, and potentially as a therapeutic target in cancer patients, appears to be a promising approach [13][14]. However, studies on the effects of physical activity, exercise programs, and weight loss on telomere length in breast cancer patients are limited, and the available findings are contradictory [15].

This study aims to compare the efficacy of in-person and telehealth cardio-oncology rehabilitation programs regarding their effect on leukocyte telomere length in breast cancer survivors.

METHODS

Study design

This prospective pilot randomized controlled study involved 90 women who had undergone comprehensive treatment for breast cancer. The study examined changes in leukocyte telomere length (LTL) during participation in comprehensive COR programs (either in-person or via telehealth) compared to a control group receiving routine clinical care.

Eligibility criteria

Inclusion criteria

Women aged 18 years and older who had undergone comprehensive treatment for breast cancer, including anthracycline-based chemotherapy and surgery, with or without radiation, targeted, or hormone therapy in accordance with current clinical guidelines. Data regarding tumor stage and molecular subtype, as well as the regimen and timing of oncology treatment, were obtained from medical documentation provided by the patients.

Exclusion criteria

Absolute contraindications to exercise testing

Withdrawal criteria

Patient refusal to continue participation in the study or to undergo follow-up monitoring.

Study setting

The study was conducted at the National Medical Research Center of Cardiology named after Academician E.I. Chazov (Ministry of Health of the Russian Federation). The patients were either referred to the center or self-referred to assess their cardiovascular status and determine cardiologic management following cardiotoxic anticancer treatment.

Study timeline

Patient recruitment and group allocation were conducted between 2021 and 2023. The follow-up period lasted for six months.

Intervention

For the in-person group, the COR program included an on-site educational course on CVD risk factors with a dietary component (a single group counseling session combined with individual counseling during weekly visits over a three-month period), an individualized exercise program twice a week for three months, and psychological support (including a single counseling session).

For the telehealth group, the COR program included an on-site educational course on CVD risk factors with a dietary component (group counseling combined with individual remote counseling once a week for three months), an individualized home exercise program with remote support for this period (including a two-week training period at the National Medical Research Center of Cardiology named after Academician E.I. Chazov), and psychological support consisting of a single counseling session. Following the baseline preventive consultation — which incorporated each patient’s individual CVD risk profile and clinical recommendations — the preferred method of remote communication (text messaging via email or a messaging application) was determined. As part of telehealth support, patients were requested to submit a weekly physical activity diary via the chosen communication channel over the three months, totaling twelve diaries. These diaries captured data on the type, frequency, duration, intensity, and tolerability of exercise, in accordance with the FITT framework. The physician analyzed these components weekly within one to two days and, if necessary, provided tailored recommendations to help patients achieve their target physical activity levels. Additionally, the physician sent text messages to monitor well-being, track reported changes, identify barriers to compliance, and provide strategies to overcome them.

For the in-person and telehealth groups, the training program was developed by an exercise physiologist based on the baseline assessment, the primary diagnosis, comorbidities, and patient preferences in accordance with current guidelines². This training regimen consisted of moderate-intensity aerobic physical activity combined with strength exercises targeting major muscle groups.

The control group was monitored in a routine clinical setting, which included standard outpatient visits to a primary care physician, adjustments to medication as needed, and general recommendations regarding physical activity levels and lifestyle modification without a structured COR program. The frequency of these visits was determined by the physician.

All study participants received lifestyle modification counseling, and their medical therapy was optimized in accordance with the current Russian national guidelines for cardiovascular prevention [16].

Study outcomes

Primary outcome

The primary endpoint of this study was the change in LTL (Δ) after six months of follow-up compared to baseline.

Secondary outcomes

Secondary endpoints included changes in clinical and instrumental variables reflecting cardiovascular status and physical performance at the six-month mark.

Outcome assessment

At baseline and the six-month mark, all included patients underwent a clinical evaluation to assess cardiovascular status and risk factors. This assessment comprised a complete blood count and a blood chemistry test to determine glucose, creatinine, and lipid profile variables, as well as the glomerular filtration rate calculated via the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Instrumental evaluations included 12-lead electrocardiography (ECG), transthoracic echocardiography, exercise ECG testing, and LTL measurement.

Physical activity levels were assessed using the WHO Global Physical Activity Questionnaire³. A sufficient level of physical activity was defined as more than 150 min of moderate-intensity or more than 75 min of vigorous-intensity physical activity per week, or an equivalent combination.

Body mass index was calculated using the following formula: BMI = body weight (kg) / height (m²). BMI values ranging from 25.0 to 29.9 kg/m² corresponded to overweight, while values of 30.0 kg/m² or higher indicated obesity.

Blood chemistry tests were performed using an ARCHITECT analyzer (Abbott, USA), and echocardiography was conducted by means of a Vivid E95 system (GE Healthcare, USA). Exercise testing was performed on a bicycle ergometer as per an incremental stepwise protocol (25 W every two minutes; n = 75) or a ramp protocol (n = 15). Cardiopulmonary exercise testing (CPET) was conducted on a Corival bicycle ergometer (Lode, Netherlands) utilizing Poly-Spectr. NET software (Neurosoft, Russia). Breath-by-breath gas analysis was performed employing a Geratherm Respiratory Ergostik system (Germany). Peak oxygen consumption (VO₂peak) was defined as the average value obtained over a 30-second period at peak exercise.

The length of chromosomal telomeric repeats was determined via quantitative real-time polymerase chain reaction (PCR) using a BIO-RAD CFX 96 Real-Time System (USA). Relative telomere length was calculated against the albumin gene, which served as the reference, using the 2^–ΔCt, formula, where ΔCt = Ct _telomeres — Ct _albumin. In this equation, Ct _telomeres represents the threshold cycle for telomeric repeat amplification, and Ct _albumin is the threshold cycle for albumin gene amplification. The resulting relative telomere length values were normalized to a calibrator (random DNA) and expressed as a percentage of the calibrator (relative units).

Randomization

Following the baseline assessment, the patients were randomized into three parallel groups of 30 participants each by an independent investigator using the sealed envelope method. A single pack of 90 identical opaque envelopes was prepared, with each containing a card with a predetermined allocation: 30 cards were designated for the in-person group, 30 for the telehealth group, and 30 for the control group. Upon enrollment, each participant sequentially drew one envelope from the pack; the contents remained concealed until the envelope was opened. The designation on the card determined the group assignment, ensuring random allocation across the three parallel groups and maintaining strict allocation concealment from the researchers conducting the observation and rehabilitation procedures.

Data de-identification

Upon receiving and processing baseline data, the authors de-identified all participant information. A new key code was assigned to the patients’ variables for the purposes of this study, without disclosing the link between the code and personal data. Subsequent analysis was conducted based on the allocation of patients across the groups: in-person, telehealth, and control.

Statistical analysis

Sample size calculation

Since this was a pilot study, the sample size was not predetermined.

Statistical methods

Statistical analysis was performed using StatTech v. 3.1.10 (StatTech LLC, Russia) and MedCalc. The normality of distribution for quantitative variables was assessed via the Shapiro–Wilk test for < 50 observations and the Kolmogorov–Smirnov test for ≥ 50 observations. Quantitative variables with a distribution not significantly different from normal (p > 0.05) were reported as the mean and standard deviation (M ± SD); in the absence of normality, they were expressed as the median and interquartile range (Me [ 25th; 75th percentiles]). Categorical data were described using absolute values and percentages. For normally distributed quantitative variables with equal variances, two-group comparisons were performed employing Student’s t-test, while three-group comparisons were executed via one-way analysis of variance followed by Tukey’s post-hoc test. For non-normally distributed quantitative variables, two-group comparisons were performed using the Mann–Whitney U test; three-group comparisons were conducted via the Kruskal–Wallis test followed by Dunn’s post-hoc test with Bonferroni correction. For the analysis of 2×2 contingency tables, a two-tailed Fisher’s exact test was used; for larger contingency tables, Pearson’s chi-square test. For paired samples, quantitative variables were compared via Student’s paired t-test for normally distributed data or the Wilcoxon signed-rank test in the absence of normality. Binary variables in paired samples were compared via McNemar’s test. The direction and strength of the association between quantitative variables were assessed employing Spearman’s rank correlation coefficient. To identify factors associated with telomere lengthening, a univariable regression analysis was performed. To determine the cut-off values for quantitative predictors, receiver operating characteristic (ROC) analysis was used, with the optimal cut-off point defined by maximizing the Youden index; these cut-offs were subsequently used to generate categorical variables. Multivariable analysis included variables that demonstrated statistically significant associations in the univariable analysis. Differences were considered statistically significant at p < 0.05.

Given the pilot study design and limited sample size, the obtained p-values were interpreted as descriptive and hypothesis-generating.

Due to the pilot nature of the study, its power was not initially calculated. However, we subsequently estimated the effect size that could be detected in a study with the observed sample size and a specified power of 80%. Calculations performed using G*Power version 3.1.9.7 (developed by Franz Faul, Kiel University, Germany) indicated that at a significance level of 0.05 and a power of 80%, differences with an effect size (Cohen’s d) of 0.9 or higher could be detected using the Mann–Whitney U test for sample sizes of 20 and 23.

RESULTS

Participant Flow and Group Allocation

The participant recruitment procedure and overall study design are presented in the flowchart (Fig. 1). The study cohort comprised women who met the eligibility criteria after undergoing comprehensive breast cancer treatment. These participants were randomized into three groups: the in-person COR group (n = 30), the telehealth COR group (n = 30), and the control group (n = 30). The COR programs included an educational course on CVD risk factors with a dietary component; an individualized program of supervised exercise twice a week for three months (in-person), an individualized home exercise program with remote support for a period of three months (telehealth); psychological support consisting of a single counseling session. The control group patients received routine clinical care.

Baseline characteristics of the study cohort

The study included 90 women who had received comprehensive breast cancer treatment (mean age: 50.7 ± 8.9 years). Detailed baseline clinical profiles for this cohort, including breast cancer subtype, anticancer treatment, cardiovascular diseases and risk factors, echocardiographic parameters, and exercise testing results, have been reported previously [17]. Selected baseline characteristics are presented in Table 1. Among conventional CVD risk factors, the most prevalent were dyslipidemia, hypertension, overweight/obesity, and abdominal obesity; less common were smoking and diabetes mellitus. More than two-thirds of the patients reported insufficient physical activity (< 150 min of moderate-intensity or 75 min of vigorous-intensity physical activity per week, or an equivalent combination). Among CVDs, heart failure was the most frequently diagnosed condition, affecting 11 (12.2%) patients. Coronary artery disease was rarely detected (1 patient), while paroxysmal atrial fibrillation and a history of pulmonary embolism were observed in three patients each. According to cardiopulmonary exercise testing, cardiorespiratory fitness was reduced, with a median VO₂peak at 71% of the predicted values.

Primary Outcomes

In the overall sample, the mean LTL was 57.4 ± 7.3 relative units. To identify variables associated with LTL in breast cancer survivors after cardiotoxic treatment, univariable and multivariable linear regression analyses were performed. In univariable models, older age (β = −0.259; p = 0.021), hypertension (β = −4.529; p = 0.019), and obesity (β = −5.804; p = 0.023) were associated with shorter LTL, whereas higher VO₂peak (β = 1.049; p = 0.004) was associated with longer LTL (Table 2).

In the primary multivariable model adjusting for age, hypertension, obesity, and VO₂peak, higher cardiorespiratory fitness (VO₂peak) remained positively associated with LTL, with a trend toward statistical significance (β = 1.059; p = 0.055; model p = 0.042), whereas the other covariates were not significant (Table 3). In subsequent models (model p < 0.05) testing various combinations of age, hypertension, and obesity, a higher VO₂peak level emerged as the sole independent predictor of greater LTL: β = 1.104, p = 0.044 in the model adjusting for VO₂peak, age, and hypertension; β = 1.103, p = 0.025 in the model adjusting for VO₂peak, age, and obesity; β = 0.908, p = 0.049 in the model adjusting for VO₂peak, hypertension, and obesity. These findings demonstrated the reproducibility of the identified association across several variants of the model, confirming the independent prognostic value of cardiorespiratory fitness as a factor linked to longer LTL.

Over the six-month follow-up, 23 patients withdrew for various reasons (Fig. 1). Baseline age, hypertension, obesity, LTL, BMI, VO₂peak, and other key clinical and functional variables did not differ significantly between patients who completed follow-up and those who discontinued (p > 0.05; data not shown), suggesting no evidence of systematic attrition bias. To assess potential bias associated with patient attrition, baseline characteristics were compared between patients who had completed the follow-up according to the protocol and those who discontinued early. The groups did not differ significantly in age, presence of hypertension or obesity, as well as baseline values of LTL, BMI, VO₂peak, and other key clinical and functional variables (p > 0.05; data not shown). This indicated the absence of any clear signs of systematic bias associated with patient attrition, allowing the final study cohort to be considered acceptable for subsequent analysis of changes in the evaluated variables.

The final analysis included data from 20 patients in the in-person group, 23 patients in the telehealth group, and 24 patients in the control group. These comparison groups demonstrated no significant differences in baseline LTL values or other primary variables evaluated (Table 4).

Changes in LTL over the six-month follow-up were analyzed across study groups. LTL increased in both COR groups; this increase reached statistical significance in the telehealth group (p = 0.008) and showed a nonsignificant trend in the in-person group (p = 0.075), whereas no significant change was observed in the control group (p = 0.579) (Table 4). At six months, mean LTL in the control group was significantly lower than in the in-person (mean difference, −6.9 relative units; 95% CI, −12.5 to −1.4; p = 0.015) and telehealth groups (mean difference, −5.4 relative units; 95% CI, −10.5 to −0.4; p = 0.035). The mean difference in ΔLTL versus the control group was −5.3 relative units (95% CI, −10.0 to −0.7; p = 0.025) for the telehealth group and −5.6 relative units (95% CI, −11.6 to 0.4; p = 0.066) for the in-person group (Fig. 2). Thus, both in terms of six-month LTL values and the magnitude of its change over the observation period, the COR groups demonstrated more favorable outcomes compared to the control group.

In logistic regression, participation in COR (in-person or telehealth) was associated with higher odds of telomere lengthening at six months compared with the control group (OR, 4.694; 95% CI, 1.436–15.350; p = 0.011).

In order to identify variables associated with telomere lengthening in COR participants after six months of follow-up, a logistic regression analysis was performed, with sequential evaluation of univariable and multivariable models. In univariable models among COR participants, higher baseline BMI and increases in cardiorespiratory fitness over follow-up (ΔVO₂peak) showed opposing associations with the odds of telomere lengthening: higher baseline BMI reduced the odds, whereas greater ΔVO₂peak increased them (Table 5).

Exploratory ROC analysis suggested preliminary cut-off points for ΔVO₂peak (1.9 mL/min/kg) and baseline BMI (25.5 kg/m²) associated with LTL increase. The BMI cut-off was close to the conventional threshold for overweight (25 kg/m²), which facilitates clinical interpretation. In the selection of this cut-off point, the statistical significance of BMI as a predictor of telomere lengthening persisted: for BMI ≥ 25 kg/m², the OR was 0.089 (95% CI: 0.016 to 0.502; p = 0.006). These threshold values remain exploratory and require validation in independent cohorts. Age, the presence of hypertension, baseline cardiorespiratory fitness, and the degree of BMI reduction demonstrated no significant associations with changes in LTL over the six-month follow-up in COR participants.

Among patients in the combined COR cohort (in-person and telehealth), a moderate negative correlation was observed between ΔLTL and baseline BMI (r = −0.469, p = 0.003, 95% CI: −0.686 to −0.176).

According to the multivariable logistic regression analysis, both variables (baseline BMI and ΔVO₂peak over the follow-up period) remained significantly associated with the odds of an LTL increase, serving as independent predictors of this outcome (Table 6).

Secondary outcomes

Secondary analyses examined changes in selected clinical variables over six months. Cardiorespiratory fitness increased significantly versus baseline in both COR groups, with no significant change in the control group. At six months, mean VO₂peak values in both COR groups exceeded those in the control group, and the improvement in VO₂peak was greater in the telehealth group than in the control group (Table 4). These data indicated a favorable improvement in the functional status of COR participants, which was most pronounced in the telehealth group.

After six months of follow-up, no statistically significant changes in blood pressure were observed in any of the groups (Table 4). Patient BMI did not change significantly in COR participants, whereas in the control group, a significant increase was observed. At the six-month mark, ΔBMI in the control group was greater than in the telehealth group (Table 4). These findings indicated less favorable BMI outcomes in the control group compared to those in the COR groups.

Adverse events

No serious adverse events occurred during the COR program.

DISCUSSION

Study limitations

Several limitations of this pilot study should be noted, including its single-center design, the limited number of patients included, and the relatively short follow-up period (six months).

It should be noted that direct comparisons of telomere length data across different investigations is challenging due to methodological variations. We used quantitative real-time PCR to determine the relative length of leukocyte telomeres. Although this method is reliable and has been widely adopted, alternative techniques have been employed in a number of studies (Southern blot, Q-FISH, flow-FISH, STELA, and STAR [digital real-time PCR]). Moreover, we assessed telomere length in leukocytes whereas other researchers utilized alternative tissues, such as muscle or saliva.

Another limitation is the absence of telomerase measurements, despite its critical role in maintaining telomere length and cellular replicative potential.

Furthermore, the study population consisted of patients who had received comprehensive cardiotoxic treatment for breast cancer; therefore, these findings cannot be directly generalized to all breast cancer survivors.

Generalizability and future directions

Future research should identify the optimal components and duration of COR programs to achieve favorable effects on telomere biology across diverse cohorts of breast cancer survivors. Such studies should account for baseline weight status (including BMI categories), physical activity, cardiorespiratory fitness, cardiovascular comorbidities, prior oncology treatment, and other relevant factors, with the ultimate goal of developing personalized rehabilitation strategies.

Summary of primary findings

In breast cancer survivors after cardiotoxic treatment, LTL was significantly associated with cardiorespiratory fitness. The efficacy of in-person and telehealth COR programs was evaluated in terms of LTL changes in this population. After six months, LTL changes differed significantly between the telehealth COR and control groups, whereas the difference between the in-person COR and control groups showed a trend toward significance. At the six-month mark, the mean LTL value in both COR groups (in-person and telehealth) was significantly higher than in the control group. High baseline BMI values decreased the odds of telomere lengthening, whereas an increase in cardiorespiratory fitness increased these odds in COR participants.

Discussion of primary findings

To our knowledge, this pilot study is among the first to comparatively evaluate the efficacy of in-person versus telehealth COR programs regarding LTL changes in patients who had undergone comprehensive cardiotoxic oncology treatment for breast cancer.

Located at the termini of eukaryotic chromosomes, telomeres are tandem DNA repeats that ensure genomic stability. However, telomeres gradually shorten with each cell division. Accumulating data indicate that the length of telomeres in leukocytes, skeletal muscle cells, and other body tissues may be positively associated with a healthy lifestyle and inversely correlated with the risk of developing age-related diseases, including CVD, cancer, obesity, and diabetes [18]. Inflammation and oxidative stress, which represent the underlying pathogenic mechanisms of CVD, accelerate telomere shortening and lead to cellular senescence [7][9][19]. Telomerase counteracts this process by maintaining and extending telomere length [7]. Clinical studies have shown that age-related diseases and conventional CVD risk factors, such as smoking, obesity, a sedentary lifestyle, and hypertension, are associated with telomere shortening [20], whereas physical activity and regular moderate- to vigorous-intensity aerobic exercise, which improve cardiorespiratory fitness, help preserve telomere length [12][21].

An association between insufficient physical activity and shorter LTL was also noted in a cohort of breast cancer patients [22]. Various systemic cancer treatments (chemo- and radiation therapy), which exert toxic effects not only on tumor cells but also on healthy tissues throughout the body, can cause additional damage to telomeres [10][11]. In this study, conventional CVD risk factors (age, hypertension, obesity) were associated with shorter LTL, whereas higher VO₂peak emerged as the only independent predictor of longer LTL in multivariable analysis. Furthermore, multivariable regression analysis revealed that a higher VO₂peak level was the sole independent predictor of longer telomere length.

The last decade has been marked by rapid advances in cardio-oncology—an interdisciplinary field of medicine whose primary objectives include reducing the risk of CVD and its complications in cancer patients [23]. The future of preventive cardio-oncology lies in the development and clinical implementation of COR programs for patients who have undergone cardiotoxic oncology treatment and present with elevated cardiovascular risk [4]. Most randomized controlled trials in the field of COR have a limited duration, which precludes a full assessment of their impact on patients’ long-term prognosis. Under these conditions, the efficacy of COR programs is assessed based on changes in variables whose association with cardiovascular outcomes has been conclusively demonstrated, primarily cardiorespiratory fitness levels and conventional CVD risk factors [5][6]. Given the available evidence linking cardiovascular risk to LTL [7], LTL may serve as a potential marker of rehabilitation program efficacy.

This study demonstrated the feasibility of lengthening leukocyte telomeres in breast cancer survivors participating in comprehensive COR programs. Additionally, an improvement in cardiorespiratory fitness (VO₂peak levels) was established in the intervention groups. Of note is that according to the logistic regression analysis, greater odds of telomere lengthening were associated with the magnitude of cardiorespiratory fitness improvement (ΔVO₂peak > 1.9 mL/min/kg) in COR participants.

Although most studies highlight the beneficial effects of physical activity on telomere length, the molecular events underlying telomere maintenance and/or elongation remain poorly understood [12]. Telomere biology is a highly complex process. Recent studies confirm that the regulation of telomere length and telomerase activity varies across different tissue and cell types. It is hypothesized that oxidative stress levels play a decisive role in telomere dynamics during physical exercise. Regular exercise strengthens the body’s endogenous antioxidant system, protecting cells from oxidative damage, thereby preserving telomere integrity [12][24][25]. In addition to oxidative stress suppression, alternative mechanisms through which physical activity and aerobic exercise may slow telomere shortening or even promote elongation include the attenuation of inflammation, increased expression of shelterin complex proteins, and enhanced telomerase activity [12][21][24].

Numerous investigations have demonstrated a positive correlation between physical activity and telomere length in healthy individuals. In a systematic review by Schellnegger et al. encompassing 43 publications (randomized controlled trials, observational studies, and interventional trials), the majority of analyzed works indicated a positive effect of regular moderate- to vigorous-intensity aerobic exercise on telomere length. However, the authors highlighted a lack of consensus regarding the most beneficial exercise type and modality (intensity, duration, and frequency) [12]. A recent meta-analysis of 22 randomized and non-randomized controlled clinical trials also noted a positive effect of physical exercise on telomere length in healthy individuals, varying by exercise duration and type. Specifically, aerobic exercise and endurance training resulted in minor improvements, while high-intensity interval training produced a moderate positive effect [25].

Although the positive effects of physical activity on cardiorespiratory fitness in cancer patients, including breast cancer survivors, have been conclusively demonstrated [26][27], studies examining the impact of physical activity, exercise programs, and weight loss, on telomere length in this population remain limited. Published findings are inconsistent, which can be largely attributed to heterogeneity across studies regarding ethnicity, the inclusion of patients at various breast cancer stages, characteristics of prior oncology treatments, menopausal status, and comorbidities (such as hypertension and obesity), as well as differences in methods for physical activity assessment, tissue samples analyzed, and LTL measurement techniques [15].

For example, Santa-Maria et al. conducted a randomized trial including 96 breast cancer survivors (Stages 0–III) with a BMI ≥ 25 to evaluate the efficacy of a 12-month telehealth intervention comprising 21 telephone consultations on weight loss and the tracking of exercise, meals, and weight via a web platform (POWER-remote). This was compared to a control group receiving standard recommendations for maintaining a healthy weight and a single professional consultation on physical activity. Participation in the telehealth program led to significant weight loss and favorably affected leptin levels, inflammatory cytokines, and lipid profile in the patients. However, at the six-month mark, no significant changes in telomere length were observed in the comparison groups [28].

In another randomized controlled trial, Sanft et al. examined the effect of a six-month weight loss intervention involving exercise and diet (comprising 150 min of moderate-intensity physical activity per week, 10,000 steps per day, and a reduction in caloric intake to 1,200–2,000 kcal per day) on telomere length in overweight or obese breast cancer survivors compared to routine care. After the six-month follow-up, the groups demonstrated no significant differences in LTL changes. However, among women with Stage 0–I breast cancer, a 7% telomere lengthening was observed in the intervention group compared to an 8% shortening in the control group (p = 0.01) [29].

In a systematic review encompassing five investigations, three demonstrated a significant association between physical activity and a slower telomere shortening [15]. The authors noted that despite study heterogeneity precluding definitive conclusions, strategies promoting increased physical activity generally yielded promising outcomes.

In this study, no statistically significant BMI changes were observed in the COR groups, whereas in the control group, an increase was noted. It can be hypothesized that the odds of telomere lengthening were reduced in patients with an elevated BMI prior to participating in COR programs. A negative correlation was identified between baseline BMI and ∆LTL over the six-month follow-up period. Our data are consistent with the findings of previously cited studies, in which obese breast cancer patients showed no significant telomere lengthening despite weight loss [28]. Similar patterns were observed in cohorts without oncological pathology. For example, in a study by Friedenreich et al. involving 212 physically inactive women, 12 months of aerobic exercise led to no significant changes in telomere length, which the authors attributed to baseline participant characteristics, such as BMI or dietary habits [30]. In another randomized controlled trial involving 439 overweight postmenopausal women, a 12-month weight-loss program combining diet and/or aerobic exercise sufficient to achieve clinically significant weight loss in most women yielded no significant effect on LTL compared to the control group. Furthermore, weight loss was not associated with LTL dynamics [31].

In a study by Dankel et al., utilizing data from the National Health and Nutrition Examination Survey for 1999–2002, participants were stratified into six groups based on physical activity levels and the duration of time spent within a specific BMI category. All physically active participants, with the exception of those who remained overweight or obese for a prolonged period (≥ 10 years), demonstrated longer telomeres compared to sedentary individuals [32].

In a randomized study, Mason et al. demonstrated that in obese individuals, leukocyte telomere lengthening was achieved following a 10% weight loss sustained over a 12-month maintenance period [33].

Thus, it can be hypothesized that obesity and the associated inflammation and oxidative stress attenuate the positive effects of exercise and diet on telomerase activity and telomere status, suggesting that modifications in LTL require longer intervention periods and sustained maintenance of a healthy body weight.

Integrating telemedicine technologies into the system of prevention, treatment, and long-term surveillance for patients with chronic noncommunicable diseases can improve the efficacy of monitoring adherence to a healthy lifestyle and optimize the management of modifiable risk factors [16][34]. For cancer patients, telehealth-delivered rehabilitation also demonstrates substantial potential and is increasingly recognized as a model equivalent in efficacy to in-person programs, while surpassing them in accessibility and proving equally safe [35].

The findings of our study suggest that a COR program with remote support can be non-inferior to an in-person program regarding its impact on cardiorespiratory fitness and LTL. The increase in LTL compared to baseline and ΔLTL differences compared to the control group reached statistical significance only in the telehealth group, whereas the in-person group demonstrated a trend toward significance. In-person COR programs have limitations due to their format and duration (requiring special conditions and typically lasting only a few weeks to months), which may preclude the development of a sustainable behavioral pattern in patients. Telehealth support facilitates better adaptation to independently maintaining new habits in daily life through regular training in a familiar setting. This approach expands opportunities for consolidating and sustaining clinical improvements. While the intervention duration in our study was three months, LTL was assessed after a six-month follow-up. It can be hypothesized that a more stable behavioral pattern, with regular exercise continuing beyond the active COR phase, contributed to the outcomes observed in the telehealth group.

CONCLUSION

For the first time in Russia, a pilot study has been conducted to evaluate the efficacy of different COR programs, including those incorporating telehealth technologies, in breast cancer survivors with respect to changes in leukocyte telomere length. The results of this study suggest that a COR program with telehealth support may be at least as effective as an in-person program in terms of its impact on cardiorespiratory fitness and leukocyte telomere length dynamics. These observations require confirmation in larger studies. The data obtained indicate a potential role of leukocyte telomere length as a genetic marker of the efficacy of rehabilitation interventions, however, the lack of standardized methods for telomere length assessment, limited availability of this technique, and the insufficient evidence base in this population currently preclude recommending this parameter for routine use in clinical practice.