Blood pressure control in older cancer patients with hypertension: a multicentre study in Vietnam

Background. High blood pressure (BP) is a common comorbidity in older patients with cancer. However, real world evidence regarding BP control among older patients with cancer remains scarce, particularly in low- and middle-income countries (LMICs). This study aimed to examine the prevalence of suboptimal control of BP among older patients with cancer in Vietnam and its key predictors. Methods. This was a cross-sectional study of cancer patients aged ≥65 years with a diagnosis of hypertension in Vietnam from 2023 to 2024. Suboptimal BP control was defined as BP ≥140/90 mmHg. To examine factors associated with suboptimal BP control, multivariable logistic regression models were employed, and the results were presented as adjusted odds ratios (aORs) and 95% confidence intervals (CIs). Results. Among 253 cancer patients with hypertension (mean age 73±6.0 years; 49.4% women), 28.1% had suboptimal BP control. On multivariable analysis, anorexia (aOR 1.93, 95%CI 1.05–3.54), dyslipidemia (aOR 1.87, 95%CI 1.04–3.36), and polypharmacy (aOR 1.82, 95%CI 1.01–3.28) were associated with higher odds of suboptimal BP control. In contrast, regular exercise (aOR 0.54, 95%CI 0.29–0.98) and severe comorbidity, a Charlson Comorbidity Index≥5 (aOR 0.47, 95%CI 0.25–0.86), were associated with lower odds of suboptimal BP control. Conclusion. In this study, over a quarter of cancer patients had suboptimal BP control, and those with conditions such as anorexia, dyslipidemia, and polypharmacy exhibited a markedly higher burden. These findings underscore the need for targeted interventions to mitigate the contributing factors to optimize BP control and improve outcomes in older patients with cancer.

Hypertension is a major modifiable risk factor for cardiovascular disease [1] and other chronic conditions, with a profound impact on disability-adjusted life-years worldwide, as highlighted in Global Burden of Disease studies[2-4]. As age increases, the prevalence of hypertension increases significantly [5, 6], being higher among older adults than among younger peers[2, 7]. Prior studies estimated that over two-thirds of participants aged ≥65 years had been diagnosed with hypertension[8-10]. Hence, monitoring high blood pressure (BP) globally is important to identify customized solutions to address high blood pressure. According to the Non-Communicable Disease Risk Factors Study 2017, the prevalence of hypertension is increasing rapidly in low- and middle-income countries (LMICs) [11]. Two-thirds of the hypertensive population live in LMICs. Thus, BP control is an important measure of progress towards achieving universal health coverage as a target of the Sustainable Development Goals, considering its high burden on LMICs[12]. Despite global efforts to manage hypertension, BP control remains a challenge, especially in older populations[13, 14]. For older adults with hypertension, it has often been reported that the risk of adverse health outcomes, including heart failure, coronary heart disease, peripheral artery disease, renal failure, stroke, and dementia in people with hypertension[16-18]. Globally, cancer is a major health challenge, contributing to substantial morbidity and mortality[19], with an estimated 20 million new cancer cases and 9.7 million cancer-related deaths by 2022[20]. Hypertension, a prevalent condition in the older population, may complicate cancer treatment and contribute to poor outcomes. In cancer patients, hypertension is the most prevalent comorbidity[21, 22] and is difficult to manage because of common underlying risk factors and the effects of anticancer therapies on blood pressure[23]. Hypertension and cancer share common underlying risk factors, such as smoking, diabetes, and obesity[24-26], as well as biological pathways, such as inflammation and immune system dysfunction[27]. Several cancers and cancer-related treatments directly cause hypertension or indirectly mediate its development [28, 29]. Poorly controlled hypertension is a major contributor to an increased risk of adverse cardiovascular events among patients with cancer [30]. Hence, controlling BP is crucial for reducing the burden of disease and improving the health outcomes of patients with cancer [23]. Assessing predictors for BP control may help identify at-risk subgroups, allowing for tailored interventions and better management strategies. To date, there is a dearth of evidence on BP control in older patients with cancer, particularly in LMICs, where healthcare resources and access to hypertension management may be limited. Therefore, we sought to estimate the prevalence of suboptimal BP control and its predictors in cancer patients in an older population in Vietnam, a middle-income Asian country. In Vietnam, the prevalence of hypertension is high among older adults; however, the rate of hypertensive individuals who are aware, treated, and controlled remains low [31, 32][33]. No prior study has investigated BP control status and factors that may influence it among older cancer patients in Vietnam. Our findings may inform policy makers and clinicians to enhance integrated care for this population by providing foundational insights into this under-explored clinical concern, which may ultimately enhance survivorship and quality of life.

This study was based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational studies [34] ( Supplementary document 1 ). The study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 676/HDDD-DHYD) and conducted in accordance with the principles of the Declaration of Helsinki. Informed consent was obtained from all participants. Study population This was a cross-sectional analytical study using data from a study on frailty in older patients with cancer in Vietnam. Details of this study have been described in a previous publication[35]. In brief, participants were recruited from the outpatient clinics of two hospitals in Ho Chi Minh City, Vietnam, between September 2023 and May 2024. Participants were eligible for the current study if they were 65 years and older and were diagnosed with cancer and hypertension. Hypertension was defined according to the 2022 Vietnamese Society of Hypertension guidelines (systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg) [36]. Additionally, a diagnosis of hypertension made by a doctor documented in the medical records or the use of antihypertensive medications also qualified as hypertension. Outcome of interest In this study, the outcome of interest was suboptimal BP control. Suboptimal BP control was defined as a systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg. These BP targets were chosen to align with the 2022 Vietnamese Society of Hypertension guidelines[36], the 2020 International Society of Hypertension guidelines[37], and the 2022 ESC guidelines on cardio-oncology[38]. Systolic BP (SBP) and diastolic BP (DBP) were measured during routine clinic visits using automated BP monitors and the most recent values were used. Study variables and measurement Data on covariates included patient demographics (age, sex, educational status, marital status), lifestyle (smoking, alcohol consumption, physical activity/exercise), cancer-related characteristics (time since diagnosis, cancer type, stage, treatment type), common geriatric syndromes, and comorbidities. Anthropometric measures (i.e., height and weight) of participants were measured during physical examination, and body mass index (BMI) was calculated by dividing weight by height squared (kg/m 2 ) and categorized as underweight (<18.5), normal (≥18.5, and < 23.0), overweight (≥23 and <25), or obese (≥25) based on the World Health Organization criteria for Asian populations [39]. Patient age was categorized into groups: 65-69, 70-74 and ≥75 years. Cancer type was determined using the International Classification of Diseases, 10th Revision (ICD-10) codes and categorized into breast, lung, colorectal, prostate, gastric, and other cancers. Living alone was defined as whether the participants indicated that they lived alone (yes or no). Information regarding current smoking status (yes/no), regular alcohol consumption (yes/no), and regular exercise (yes/no) was obtained from a self-reported questionnaire. Regular exercise was defined as being engaged in physical activity for at least five days per week. Comorbidities were documented from the medical records based on a predefined list, including coronary heart disease (CHD), heart failure (HF), stroke, dyslipidemia, type 2 diabetes, chronic kidney disease (CKD), osteoarthritis, asthma, chronic obstructive pulmonary disease (COPD), gastroesophageal reflux disease (GERD), musculoskeletal pain, sleep disorder, anorexia, cognitive decline, and obesity, identified based on ICD-10 diagnosis codes. Cognitive function was assessed using a 6-item Blessed Orientation-Memory-Concentration (BOMC) test, and a BOMC score ≥5 was defined as cognitive decline[40]. Anemia was defined as a serum hemoglobin concentration of <12 g/dL for women and < 13 g/dL for men[41]. The overall comorbidity burden was assessed using the Charlson Comorbidity Index (CCI)[42]. The severity of comorbidity was recorded according to the CCI as severe (CCI≥5) or mild/moderate (CCI<5)[43]. Participants were assessed for common geriatric syndromes, including frailty, polypharmacy, depression, malnutrition, fall risk, impairment in activities of daily living (ADL), and instrumental activities of daily living (IADL). Frailty was defined using the Carolina Frailty Index (CFI),[44] and participants with a CFI >0.35 were considered frail[44]. Polypharmacy was defined as using 5 or more medications daily basis [45]. Depression was defined using the Geriatric Depression Scale (GDS), with a GDS score ≥5 indicating depression[46]. We assessed the nutritional status using the Mini Nutritional Assessment Short Form (MNA-SF), and participants with a score ≤7/14 were identified as having malnutrition[47]. The Stopping Elderly Accidents, Deaths, and Injuries (STEADI) questionnaire [48] was used to assess the risk of falls, and participants who answered yes to any of the three questions were identified as having a high risk of falls. ADLs and IADLs were assessed using questionnaires, and participants with an ADL score <6 were identified as having ADL impairment, whereas those with an IADL score <8 were identified as having IADL impairment[49]. Statistical analysis We summarized the characteristics of the participants overall and stratified by BP control status and reported using mean (±SD) or number (%) for continuous and categorical variables, respectively. We compared between-group differences using the chi-square test or Fisher’s exact test for categorical variables, and Student’s t-test, Wilcoxon test, or ANOVA for continuous variables. We estimated the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the factors associated with suboptimal BP control using logistic regression analysis. Univariate logistic regression was conducted for all potential variables that could be associated with suboptimal BP control, and variables significant at p-values [50]. The final model contained only variables with p-values of 17.0 and SPSS 29.0. Statistical significance was defined as a two-sided p-value of <0.05. Participant characteristics Supplementary Figure 1 shows a flowchart defining the samples used in this analysis. In total, 253 patients with cancer and hypertension were included in the analysis. The characteristics of the participants according to BP control status are shown in Table 1 . The participants had a mean age of 73.0 (±6.0) years, ranging between 65 and 87 years, and 50.6% were male. Most participants (77.1%) lived in urban areas and 5.9% lived alone. Regarding lifestyle factors, 22.1% were current smokers, 9.9% were regular alcohol users, and 41.5% engaged in regular exercise. The most common comorbidities were anemia (64.8%), musculoskeletal pain (56.5%) and dyslipidemia (47.4%). The most common cancer types were colorectal, breast, and lung; 31.2% of the participants were within the first 3 months after their cancer diagnosis, 22.9% were between 3 months and 12 months, 23.7% were between 1 and 3 years, and 22.1% had been diagnosed for more than 3 years. Prevalence of suboptimal BP control Overall, the prevalence of suboptimal BP control was 28.1% (95%CI: 22.5% - 33.6%), whereas 71.9% (95% CI: 66.1% - 77.2%) achieved optimal control. The mean SBP was 141 ± 7.4 mmHg in the suboptimal BP group, compared to 120.4 ± 8.4 mmHg in the optimal group (p<0.001), while the mean DBP was 80.9 ± 8.1 mmHg in the suboptimal BP group compared to 71.4 ± 6.6 mmHg in the optimal group (p<0.001). There was no statistically significant variation in the mean SBP and DBP across the sex and age groups ( Figure 1 and 2 ). Differences in lifestyles, comorbidities, and geriatric syndromes in suboptimal and optimal BP groups Patients with suboptimal BP were less likely to exercise regularly (31.0% vs. 45.6%, p=0.034) and less likely to present with severe comorbidity (29.6% vs. 44.5%, p=0.030) compared with those with optimal BP control. Patients with suboptimal BP control had a significantly higher prevalence of dyslipidemia (59.2% vs. 42.9%, p = 0.020) and anorexia (39.4% vs. 26.4%, p = 0.042) compared with those with optimal BP. There were no significant differences in the other characteristics between the two groups ( Table 1 ). Figure 3 shows the prevalence of geriatric syndromes in both the groups. Polypharmacy was significantly higher in participants with suboptimal BP compared to those with optimal BP (56.3% vs. 40.7%, p=0.024). However, there was no significant difference in the remaining geriatric syndromes between the two groups. Predictors of suboptimal BP control The unadjusted logistic regression analysis is presented in Table 2. In the multivariable model, patients with anorexia (adjusted OR 1.93, 95%CI: 1.05-3.54), polypharmacy (adjusted OR 1.82, 95%CI: 1.01-3.28), and dyslipidemia (adjusted OR 1.87, 95%CI: 1.04-3.36) had higher odds of having suboptimal BP control compared with those without these conditions. In contrast, patients with regular exercise (adjusted OR 0.54, 95%CI: 0.29-0.98) and severe comorbidity (adjusted OR 0.47, 95%CI: 0.25-0.86) had lower odds of suboptimal BP control compared with their counterparts. ( Figure 4 )

To the best of our knowledge, this is the first study to investigate the prevalence of suboptimal BP control and to identify key predictors in older cancer patients with hypertension in Vietnam. In this study of 253 older cancer patients with hypertension, we found that more than a quarter (28.1%) of the participants had suboptimal BP control - highlighting a significant unmet clinical need within the complex context of geriatric oncology. Our findings support the limited number of prior studies reporting suboptimal BP control rates among cancer survivors. For example, in an analysis of 442 cancer survivors (mean age 57.7 ± 4.7 years) from the Polish Norwegian Study, Vaidean and colleagues reported that 24.2% of them had suboptimal control of BP [51]. Another study using electronic health records from 127 urban primary care practices in the UK reported that suboptimal BP control rate was 32% among 8340 cancer survivors (mean age 72.1±11.3 years) [52]. However, other studies have reported a higher rate of suboptimal BP among cancer patients. For example, a cross-sectional analysis of 90,494 US veterans with prostate cancer showed that 35.7% had uncontrolled BP[53]. In another study conducted by Klimis and colleagues involving 2811 men (mean age 68.3 ± 8.0) with prostate cancer across Canada, Australia, Israel, and Brazil, three-quarters of the patients had suboptimal BP control[54]. The discrepancy in reported BP control rates may reflect differences in factors such as patient age, geographical settings, cancer types, hypertension, and comorbidities definitions. Considering these discrepancies, regular monitoring of BP is important in patients with cancer to ensure timely detection. Our analysis identified key predictors that were significantly associated with suboptimal BP control among patients with cancer. We found an association between anorexia, polypharmacy, and dyslipidemia and higher odds of suboptimal BP control, while regular exercise and severe comorbidities were associated with lower odds of suboptimal BP control. Our results represent one of the first to quantify anorexia in patients with cancer, highlighting the impact of nutritional status. Anorexia, often a sequela of cancer and its treatment, can lead to muscle wasting and electrolyte imbalance, which can disrupt BP regulation. Cancer-related anorexia is common in patients with cancer and may have significant impacts on their daily activities, their mood and medication adherence [55, 56]. In our study, 30% of the participants had anorexia, emphasizing the need for effective management of anorexia to improve BP control. The observed association between suboptimal BP control and polypharmacy is critical. Reviews in older cancer cohorts link polypharmacy to drug–drug interactions and poorer cardiovascular outcomes, although BP control is seldom the primary endpoint [57]. Polypharmacy can complicate BP treatment due to increased medication (drug-drug) interactions, which may reduce the effectiveness of antihypertensive drugs and increase adverse effects [58]. This can lead to cessation or change in antihypertensive medications or reduce medication adherence. About half of the participants in our study experienced polypharmacy, highlighting the need for regular medication reviews to identify and deprescribe unnecessary medications, switch to drugs with fewer interactions, adjust dosages, or use a single-pill combination for hypertension to simplify regimens [58]. The association between dyslipidemia and suboptimal BP control among our study participants is consistent with prior studies [59-61]. Metabolic risk factor clustering (the coexistence of hypertension and dyslipidemia) is often observed in clinical practice [62]. Uncontrolled lipid levels in older patients can worsen arterial stiffness and complicate BP management. In contrast, we found that regular exercise and severe comorbidities were associated with lower odds of suboptimal BP control. Although growing evidence supporting the beneficial effects of physical activity on hypertension prevention [61, 63], the exact mechanisms by which physical activity lowers BP remain incompletely understood. The proposed hypotheses include alterations in insulin sensitivity, autonomic nervous system function, and vasoconstriction regulation [64]. Regular exercise has been linked to improvements in cardiorespiratory fitness, enhanced endothelial function, and reduced systemic inflammation, and may contribute to optimizing BP control [65]. Lifestyle modifications, such as regular physical activity, are generally beneficial for BP control in the general population and should be encouraged in cancer patients [66]. In addition, the optimal prescription of physical activity for BP control is unknown, which leaves a critical gap in current guidelines and underscores the need for tailored exercise prescriptions that consider the specific needs and limitations of patients with cancer. The relationship observed between severe comorbidity and suboptimal BP control is an important clinical consideration in managing hypertension in the cancer population, warranting further studies to elucidate the underlying mechanisms for this association. This association may be related to more frequent interactions with the healthcare system and/or appropriate management of those at a higher cardiovascular risk [67]. Severe comorbidities often complicate BP treatment and may lead doctors to cautiously tailor the approach, sometimes aiming for higher BP targets to balance the benefits of BP control with the risks of adverse outcomes such as hypotension and falls [68]. Additionally, patients with severe comorbidities may have frequent healthcare visits, resulting in closer BP monitoring and careful management to avoid over- or under-treatment. Patients with multiple comorbidities are typically on multiple medications (polypharmacy), which increases the risk of drug interactions and the adverse effects of antihypertensive medications. Implications This study had several important clinical implications. These results indicate the need for tailored treatment strategies that may enhance BP control and improve outcomes in cancer patients, particularly in LMICS with a high burden of comorbidities. By optimizing BP control, healthcare providers can improve cancer treatment outcomes, reduce cardiovascular risks, and enhance the quality of life of older patients with cancer. The observed prevalence of suboptimal BP control in our study likely reflects, and may even underestimate, the challenges faced in many LMICs, where healthcare infrastructure, access to diagnostic tools, and consistent medication supply are often constrained. The presence of identified risk factors, along with the need for interventions, raises significant concerns, as these countries navigate the complexities of the epidemiological transition. The management of these comorbidities along with cancer in resource-limited settings presents a significant challenge. Our findings could inform future research aimed at improving BP control and may contribute valuable insights into the limited evidence of potential predictors. Furthermore, this finding may help identify individuals who could benefit from targeted clinical practice improvement efforts. Overall, there is a pressing need for more robust quality improvement programs to improve BP control in older cancer patients. Strengths and limitations This is one of the first analyses of BP control in older cancer patients with hypertension in LMICs using comprehensive clinical data to highlight the challenges of managing hypertension in this population. However, our study has several notable limitations. In line with the general limitations of cross-sectional studies, the possibility of residual confounding and potential overestimation of some associations due to the use of odds ratios instead of prevalence ratios cannot be ruled out. The cross-sectional design also restricts our ability to establish causality between identified predictors and BP control. In addition, the absence of data regarding the duration of hypertension, use of antihypertensive medications, and medication adherence is a critical gap, as these factors may play a substantial role in BP control. Therefore, generalization of the findings from this study to other older populations should be approached with caution. Some variables were self-reported and could not be objectively verified at the time of the study, which may have resulted in differential misclassifications. Moreover, the sample size prevented us from performing subgroup analysis by covariates (such as cancer type, stage, and sex). Finally, we did not examine the impact of dietary-related factors (salt intake, fruit, and vegetable consumption), race/ethnicity, and family history of hypertension on BP control in our study population, as this information was not available in our dataset. Further large-scale studies that consider these factors are required to develop appropriate preventive strategies.

We observed that over a quarter of older cancer patients exhibited suboptimal BP control, and those with conditions such as anorexia, dyslipidemia, and polypharmacy carried a higher burden, suggesting potential gaps in BP monitoring. This study contributes to the limited understanding of the predictors of BP control in older cancer patients and highlights the importance of BP control in high-risk populations to encourage proactive BP management. Our findings call for integrated care models that prioritize the comprehensive management of hypertension in older cancer patients, particularly in LMICs where these challenges are worsening. Implementing evidence-based strategies to optimize BP control may improve cardiovascular and oncological outcomes in older patients with cancer and hypertension. Future studies should identify context-specific interventions and translate them into clinical practice and guideline development. Conflicts of interest There are no conflicts of interest. Contributions EA and TN conceived of the analyses. EA and TN conducted the statistical analyses. EA performed literature review and wrote the manuscript. All authors were involved in the data interpretation. The manuscript has been revised for important scientific content by all authors. All the authors approved the final version of the manuscript. Funding . This study received no funding. Data Availability Statement . The data supporting the findings of this study are available upon request from the corresponding author. The data were not publicly available because of privacy or ethical restrictions.

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Participants characteristics according to blood pressure control status | Age, years (mean± SD) | 73.0 ± 6.0 | 72.9 ± 6.1 | 73.1 ± 5.8 | 0.784 | | Age group | |||| | 65-69 | 93 (36.7%) | 66 (36.3%) | 27 (38.0%) | 0.665 | | 70-74 | 67 (26.5%) | 51 (28.0%) | 16 (22.6%) | | | ≥ 75 | 93 (36.8%) | 65 (35.7%) | 28 (39.4%) | | | Sex | |||| | Male | 128 (50.6%) | 93 (51.1%) | 35 (49.3%) | 0.797 | | Female | 125 (49.4%) | 89 (48.9%) | 36 (50.7%) | | | Residence | |||| | Rural | 58 (22.9%) | 43 (23.6%) | 15 (21.1%) | 0.671 | | Urban | 195 (77.1%) | 139 (76.4%) | 56 (78.9%) | | | Education | |||| | Primary | 44 (17.4) | 33 (18.1%) | 11 (15.5%) | 0.663 | | Secondary school | 149 (58.9) | 104 (57.1) | 45 (63.4) | | | Higher education | 60 (23.7) | 45 (24.7%) | 15 (21.1%) | | | Living alone | 15 (5.9%) | 11 (6.0%) | 4 (5.6%) | 0.901 | | Current smoking | 56 (22.1%) | 37 (20.3%) | 19 (26.8%) | 0.268 | | Regular alcohol use | 25 (9.9%) | 18 (9.9%) | 7 (9.9%) | 0.994 | | Regular exercise | 105 (41.5%) | 83 (45.6%) | 22 (31.0%) | 0.034 | | BMI (mean± SD) | 22.4 ± 3.3 | 22.6 ±3.2 | 22.9 ±3.3 | 0.150 | | BMI group | |||| | <18.50 | 29 (11.5%) | 22 (12.1%) | 7 (9.9%) | 0.500 | | 18.50 - 22.99 | 121 (47.8%) | 91 (50.0%) | 30 (42.2%) | | | 23.00 - 24.99 | 58 (22.9%) | 40 (22.0%) | 18 (25.3%) | | | ≥ 25.0 | 45 (17.8%) | 29 (15.9%) | 16 (22.5%) | | | Systolic BP (mmHg) | 126.2 ± 12.3 | 120.4 ± 8.4 | 141 ± 7.4 | <0.001 | | Diastolic BP (mmHg) | 74.0 ± 8.2 | 71.4 ± 6.6 | 80.9 ± 8.1 | <0.001 | | Comorbidities | |||| | Anemia | 164 (64.8%) | 119 (65.4%) | 45 (63.4%) | 0.764 | | Musculoskeletal pain | 143 (56.5%) | 102 (56.0%) | 41 (57.7%) | 0.806 | | Dyslipidemia | 120 (47.4%) | 78 (42.9%) | 42 (59.2%) | 0.020 | | Sleep disorder | 106 (41.9%) | 72 (39.6%) | 34 (47.9%) | 0.228 | | Coronary heart disease | 83 (32.8%) | 64 (35.2%) | 19 (26.8%) | 0.201 | | Diabetes | 77 (30.4%) | 49 (26.9%) | 28 (39.4%) | 0.052 | | Anorexia | 76 (30.0%) | 48 (26.4%) | 28 (39.4%) | 0.042 | | Cognitive decline | 70 (27.7%) | 48 (26.4%) | 22 (31.0%) | 0.461 | | Osteoarthritis | 47 (18.6%) | 34 (18.7%) | 13 (18.3%) | 0.946 | | GERD | 30 (11.9%) | 23 (12.6%) | 7 (9.9%) | 0.539 | | Heart failure | 14 (5.5%) | 10 (5.5%) | 4 (5.6%) | 0.965 | | Chronic kidney disease | 12 (4.7%) | 9 (4.9%) | 3 (4.2%) | 1.000 | | Stroke | 8 (2.2%) | 6 (3.3%) | 2 (2.8%) | 1.000 | | Asthma/COPD | 4 (1.6%) | 4 (2.2%) | 0 (0) | 0.334 | | CCI | 4.0 ± 2.0 | 4.2 ± 2.1 | 3.7 ± 1.8 | 0.085 | | CCI ≥5 | 102 (40.3%) | 81 (44.5%) | 21 (29.6%) | 0.030 | | Cancer types | |||| | Colorectal | 75 (29.6%) | 52 (28.6%) | 23 (32.4%) | 0.618 | | Breast | 51 (20.2%) | 33 (18.1%) | 18 (25.4%) | | | Lung | 43 (17.0%) | 33 (18.1%) | 10 (14.1%) | | | Prostate | 22 (8.7%) | 16 (8.8%) | 6 (8.5%) | | | Stomach | 17 (6.7%) | 12 (6.6%) | 5 (7.0%) | | | Others* | 45 (17.8) | 36 (19.8) | 9 (12.7) | | | Cancer stage | |||| | 0-1 | 42 (16.6%) | 25 (13.7%) | 17 (23.9%) | 0.205 | | 2 | 73 (28.9%) | 52 (28.6%) | 21 (29.6%) | | | 3 | 42 (16.6%) | 33 (18.1%) | 9 (12.7%) | | | 4 | 96 (37.9%) | 72 (39.6%) | 24 (33.8%) | | | Time since cancer diagnosis | |||| | 3 years | 56 (22.1%) | 37 (20.3%) | 19 (26.8%) | BP: Blood pressure; BMI: Body mass index; CCI: Charlson Comorbidity Index; COPD: Chronic obstructive pulmonary disease; GERD, gastroesophageal reflux disease. Continuous data are presented as mean ± standard deviation or n (column %) for categorical data. P-values were calculated using a chi-square test or Fisher’s exact test for categorical variables and Student’s t-test or Wilcoxon test for continuous variables for between-group comparison. *: Other cancers include liver, cholangiocarcinoma, oral, esophageal, thyroid, thymus, pancreatic, kidney, bladder, prostate, cervical, and ovarian cancers. Table 2. Univariate logistic regressions analysis of factors associated with suboptimal blood pressure control | Age (ref: 65-69) | || | 70-74 | 0.76 (0.37–1.57) | 0.469 | | ≥75 | 1.05 (0.56–1.97) | 0.872 | | Sex (ref: male) | || | Female | 1.08 (0.62–1.86) | 0.797 | | Rural (ref: urban) | 0.87 (0.45–1.68) | 0.671 | | Low education (ref: higher) | 0.83 (0.39 – 1.74) | 0.619 | | Living alone | 0.93 (0.29–3.02) | 0.901 | | Smoking | 1.43 (0.76–2.71) | 0.270 | | Regular alcohol consumption | 0.99 (0.40–2.50) | 0.994 | | Regular exercise | 0.54 (0.30–0.96) | 0.035 | | Obesity | 1.47 (0.75–2.91) | 0.264 | | Coronary heart disease | 0.67 (0.37–1.24) | 0.202 | | Heart failure | 1.03 (0.31–3.39) | 0.965 | | Stroke | 0.85 (1.17–4.32) | 0.845 | | Dyslipidemia | 1.93 (1.11–3.37) | 0.021 | | Diabetes | 1.76 (0.99–3.15) | 0.053 | | Chronic kidney disease | 0.85 (0.22–3.23) | 0.809 | | Osteoarthritis | 0.98 (0.48–1.98) | 0.946 | | GERD | 0.76 (0.31–1.85) | 0.540 | | Cognitive decline | 1.25 (0.69–2.29) | 0.462 | | Anemia | 0.92 (0.52–1.62) | 0.764 | | Musculoskeletal pain | 1.07 (0.62–1.87) | 0.806 | | Sleep disorder | 1.40 (0.81–2.44) | 0.229 | | Anorexia | 1.82 (1.02–3.24) | 0.043 | | Charlson Comorbidity Index ≥5 | 0.52 (0.29–0.94) | 0.031 | | Frailty | 0.76 (0.41–1.42) | 0.395 | | IADL impairment | 0.65 (0.38–1.14) | 0.138 | | Polypharmacy | 1.88 (1.08–3.28) | 0.025 | | Malnutrition | 0.57 (0.25–1.31) | 0.187 | | Depression | 0.32 (0.07–1.45) | 0.140 | | High risk of falls | 0.72 (0.41–1.27) | 0.255 | | Cancer types (ref: colorectal) | || | Breast | 1.23 (0.58–2.62) | 0.587 | | Lung | 0.68 (0.29–1.62) | 0.389 | | Prostate | 0.56 (0.23–1.36) | 0.204 | | Stomach | 0.84 (0.29–2.44) | 0.760 | | Others | 0.94 (0.29–2.98) | 0.919 | | Cancer stages (ref: stage 0–1) | || | Stage 2 | 0.59 (0.27–1.32) | 0.200 | | Stage 3 | 0.40 (0.15–1.05) | 0.062 | | Stage 4 | 0.49 (0.23–1.06) | 0.070 | | Advanced stage (ref: early) | 0.64 (0.37–1.11) | 0.109 | | Time since cancer diagnosis (ref: 3 years | 1.42 (0.67–2.99) | 0.358 | | Time since cancer diagnosis ≥1 year (ref: <1 year) | 1.66 (0.96–2.89) | 0.071 | Abbreviations: BMI: body mass index; CI: confidence interval; GERD: gastroesophageal reflux disease; IADL: instrumental activities of daily living; OR: Odds ratio. Figure 1 . Mean systolic blood pressure (and 95% confidence interval) by age group and sex Figure 2 . Mean diastolic blood pressure (and 95% confidence interval) by age group and sex Figure 3 . Prevalence of common geriatric syndromes according to BP control status IADL, instrumental activities of daily living; ADL, activities of daily living Figure 4. Associated factors of suboptimal blood pressure control in older cancer patients CI, confidence interval. Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Metrics & Citations Metrics Article Usage 271views 146downloads Citations Download citation Erkihun Amsalu, Tan Nguyen, Quyen Tran HH, et al. Blood pressure control in older cancer patients with hypertension: a multicentre study in Vietnam. Authorea. 10 September 2025. 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