Pharmacotherapy and Determinants of Asthma Control in Eastern Africa

Pharmacotherapy and Determinants of Asthma Control in Eastern Africa | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 17 June 2025 V1 Latest version Share on Pharmacotherapy and Determinants of Asthma Control in Eastern Africa Authors : Kefyalew Getahun , Nega Birhane , Winters Muttamba , Levicatus Mugenyi , Jeremiah Chakaya , Amsalu Bekele , Solomon Mequanente Abay , Tesfaye B. Mersha 0000-0002-9189-8447 , Getnet Yimer , and Bruce J. Kirenga [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175016327.71023857/v1 179 views 92 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background: Asthma, a heterogeneous disease with genetic and environmental factors interplay. High dose inhaled corticosteroids recommended for severe asthma. However, global data on medicine use and outcomes is limited Purpose: To identify asthma control predictors in one-year Eastern African cohort Design: Multicounty prospective cohort study design was used in three specialized hospitals. Asthmatic patients were followed for one year with standard treatment of care. The primary outcome was asthma control level and its predictors during follow-up. A generalized linear mixed model was used to determine predictors of asthma control. Result: Of 1521 study participants 1074 (71%) were female. Controller medicines most frequently used were budesonide with formoterol inhalers and fluticasone propionate. During follow-up participants medicines adherence rate were high, medium and low, 69%, 21%, and 10% respectively. Asthma control during follow-up was 68% (95% CI: 66.66, 68.55) representing 47% improvement compared to the baseline. High level of adherence (p<0.001), low dose fluticasone (p<0.001), higher budesonide doses (p<0.001) were associated with increased asthma control. High dose of fluticasone propionate (p<0.001) and low dose budesonide + formoterol (p<0.001) were negatively associated with asthma control. Despite high adherence, 35% of participants failed to control their asthma. Conclusion: The study demonstrated significant improvements in asthma control during follow-up. Study participants who received low dose had six-fold greater odds of having well-controlled asthma. High adherence demonstrated a two-fold asthma controlled compared to low. Implications: Despite improved asthma control over time, one-third of participants remained uncontrolled, underscoring personalized treatment needs. The finding suggests reconsidering corticosteroid doses. Key Words: Asthma, Asthma Control, Eastern Africa, Pharmacotherapy, Predictors Pharmacotherapy and Determinants of Asthma Control in Eastern Africa Kefyalew Ayalew Getahun 1 , Nega Birhane 2 , Winters Muttamba 3 , Levicatus Mugenyi 3,4 , Jeremiah Chakaya 5 , Amsalu Bekele 6 , Solomon Mequanente Abay 7 , Tesfaye B. Mersha 8 , Getnet Yimer 9 , Bruce J. Kirenga 3 Author affiliations 1 Department of Pharmacology, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia 2 Department of Medical Biotechnology, Institute of Biotechnology, University of Gondar, Gondar Ethiopia 3 Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda 4 MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda 5 Kenya Association of Physicians against TB and Lung Diseases (KAPTLD), College of Health Sciences, Nairobi, Kenya 6 Department of Internal Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia 7 Department of Pharmacology, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia 8 Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati, Cincinnati, OH, 45229, USA 9 Department of Genetics and Center for Global Genomics and Health Equity, Perelman School of Medicine, University of Pennsylvania, USA Corresponding author: Bruce J. Kirenga, MBChB, PhD, FRCP, Makerere University Lung Institute, College of Health Sciences, Mulago Hill Road, Kampala, Uganda. E-mail: [email protected] Background Asthma is a heterogeneous disease with a typical characteristics of chronic airway inflammation, a history of recurrent respiratory symptoms mainly wheezing, chest tightness, shortness of breath, and coughing that fluctuate in intensity and over time with variable airflow obstruction. 1 2, 3 These symptoms are caused by bronchial constriction due to hyper reactivity, eosinophilic infiltration, inflammation, and increased mucus production causing intermittent airway obstruction. 2 In the state of clinical control of severe asthma today associated hazards include uncontrolled asthma that lead to persistent morbidity such as children’s delayed lung growth or decreased lung function, severe exacerbations even death, and/or adverse drug reactions 4 . The three groups included are difficult-to-treat severe asthma, untreated severe asthma and treatment-resistant severe referred as refractory asthma. 4, 5 Pharmacotherapy of severe asthma: high-dose inhaled corticosteroids and a second controller (and/or systemic corticosteroids) are required to prevent or from getting worse. 6 According to 2022 World Asthma Report, asthma is still the most prevalent non-communicable disease in adolescents and children continue to be a global health concern with high burden in Africa. 7 Currently 340 to 400 million people are suffering from asthma worldwide. 2, 7-9 Currently in Africa overall prevalence of wheezing was 13.2% while in American region was 10.0%. The pooled uncontrolled asthma in Ethiopia showed 45%. 10 In Kenya and Uganda uncontrol asthma was 26.2% and 67% respectively. 11, 12 Our group reported severe asthma in teenagers and adults in Eastern Africa was 34.6%. 13 However, prediction showed that the global asthma prevalence seems stable 14 Current clinical practice, drug development, and regulation face significant challenges due to variability in drug efficacy, safety and treatment response. 15 Genetics and environmental are main factors for asthma onset and its complex nature. 2, 16 Asthma control is very poor across the globe because of phenotypic and genotypic attributes. Phenotypic asthma control predictors include poor medicines adherence 4, 7 , improper inhalational techniques, low access to medicines, environmental factors; smoking 4 and social factors. 17 T-helper type2 (Th2) cells phenotype 18, 19 , baseline eosinophil, poor lung function and comorbidities are risk factors of treatment outcomes. 19 In moderate to severe asthmatics non-response to pharmacotherapy ranges 30 to 70% despite compliance with inhaled corticosteroids (ICS) plus long acting β 2 -adrenergic receptor agonist (LABA) dictating asthma’s refractory nature and genetics might be factors. 17, 20-22 African Severe Asthma Project (ASAP) cohort characterized asthma burden in the region at baseline and one year follow up with standard treatment of care of 1671 asthmatic patients as per Global Initiative for Asthma (GINA) recommendation. 1, 13, 23 GINA guidelines recommend optimal controller LABA and ICS medicines for moderate to severe asthma. 1, 3 However, there is a global dearth of information on medicines used, their adherence and outcomes 7,21 , in particular scanty findings in Africans using longitudinal cohort. Therefore, the objectives this study were to determine asthma control level and its predictors, spirometry, medicines used and their adherence in one-year follow-up longitudinal cohort following treatment with the ICS-LABA combination or ICS and add-on therapies in Eastern African. Material and Methods Study setting and Design ASAP was prospective study aimed to explore clinical, immunology and genetics factors in Eastern Africa. A longitudinal prospective cohort study design spanning multiple countries was conducted to evaluate for changes of potential predicting factors to determine asthma control level at Black Lion Specialized Hospital, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia; Kenyatta National Specialized Hospital, Nairobi, Kenya; and Mulago Specialized Hospital, College of Health Sciences, Makerere University, Kampala, Uganda. Data collection and detailed methods have been previously reported. 13, 23, 24 Patients were diagnosed by pulmonologists at each site and on standard treatment of care (GINA) 1 and followed monthly for the first six months, 9 th , and 12 th targeting to control their asthma. Data from follow-up participants were analyzed and baseline as needed. Participants who had baseline sociodemographic, spirometry, clinical characteristics, and baseline and at least one follow-up visit from each site were included. Additionally, utilized medicines completeness, adherence level, asthma control at baseline and follow-up were used as criteria. Biomarkers: fractional exhaled nitric oxide (FeNO) 25 , Th2 26 and Th2- high were conducted. Accordingly, we determined the final nested sample size of 1,521 (357 from Ethiopia, 388 Kenya and 776 Uganda) asthmatics who met the criteria ( Figure 1) . Incomplete baseline data, single visit, patients lacking either prebronchodilator or post bronchodilator spirometry were excluded. Place Figure 1 here Spirometry Spirometry was performed at each hospital in accordance with the joint criteria of American Thoracic Society (ATS) and European Respiratory Society (ERS) using a Pneumotrac spirometer with Spirotrac V software (Vitalograph Ltd., Buckingham, United Kingdom). 13, 27 The new innovative spirometry category was used to compute forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), the ratio of FEV1 to FVC and their delta change. 28 29 We calculated spirometry dynamics ( Table 1) or bronchodilator response using modified version of formula described by Sanja Stanojevic et al 30 as follows. \begin{equation} Bronchodilator\ Resposnsiveness=\frac{Post\ brochodilator-Pre\ bronchodilator}{\text{Post\ bronchodilator}}x100\nonumber \\ \end{equation} Asthma Control Assessment Asthma control questionnaire was employed to assess asthma control level. 20, 27 Detailed used parameters were previously reported. 13, 23 Based on their outcome participants were dichotomized as well controlled and uncontrolled asthma. Asthma Medicines Adherence Measurement We used 8-item Morisky Medication Adherence Scale, the most commonly used, validated and dependable tool. 31 Depending medicines adherence participants were categorized as high, medium, and low adherence level if they scored 8, less than 8 to > 6, and 6 points scale out of eight respectively. 32 Statistical Analysis Stata version 17 was employed for quality control and analysis. The data was skewed so median with interquartile range (IQR) with confidence interval (CI) for continuous and frequencies for categorical variables employed. Prebronchodilator and post bronchodilator spirometry were computed using paired t-test and Pearson’s chi- square (χ 2 ) test for proportions. A generalized linear mixed effect model (GLMM) was fitted with logit link function and Bernoulli family to analyze asthma control level and identify predictors considering the correlation between repeated measurements on individual participant over time, multisite and hierarchical of the data. Using GLMM, fixed and random effects correlation were effectively controlled. 33, 34 To check the intercorrelation of repeated measurement intra-class correlation coefficient (ICC) was applied. The lowest Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) were chosen as the final model GLMM fitting with 95% CI for bi-variable and multivariable analysis to identify the independent predictors of asthma control level. Then we reported the findings using odds ratio (OR) with 95% CI. A p-value of < 0.05 regarded as statistically significant. Ethical considerations Ethical approval was granted from Mulago Hospital Research and Ethics Committee (MHREC 875), Uganda National Council for Science and Technology, Ethiopian Institutional Review Board (AAUMF-01-008), and Kenyatta National Hospital–University of Nairobi Ethics Review Committee (327/04/2016). Written informed consent was provided by every patient for age ≥ 12 years old, and assent was obtained from their guardians for those who were under 18 years old. Patients Characteristics The study analyzed baseline and follow-up clinical data from 1521 participants, excluding 150 cases with a single visit. For detailed nesting in each month see Figure 1 . The median age of participants was 40 years old with IQR 26 to 52 with variation among countries. Two-third of participants were female. The sociodemographic, asthma comorbid, and spirometry dynamics are shown in Table 1 . Of the participants: 48.84% were married, 22.76% single, 11.04% adolescents, 8.97% separated, and 8.39% widowed. Current occupation: 269 (17.72%), 238 (15.68%), 235 (15.48%), 228 (15.02%), 207 (13.64%) and 341 (22.46%) were students, unemployed, business owners, housewife, professionals and others consecutively. We computed ICC to assess reliability and correlation of repeated measurements taken eight times. The ICC was found to be 0.35 (95% CI: 0.27, 0.42), indicating a high level of correlation among repeated measurements taken over time from the same participant. The best fitted model, AIC and BIC results are shown in Table 2 . Spirometry Spirometry result of FEV1, FVC, and FEV1/FVC differences of pre- and post-bronchodilator and their delta changes in mean and median with IQR, mean delta change (95% CI) and mean % change (95% CI) ( Table 1) . FEV1 was also calculated following the new five novel category and shown in the same table. Place table 1 Here Utilized Medicines Study participants were treated with budesonide plus formoterol inhaler, fluticasone propionate inhaler, beclomethasone plus LABA and other medicines: 40.95%, 38.88%, 10.25% and 3.56% respectively. Of participants who treated with inhaled fluticasone propionate 29.40%, 40.55% and 26.05% had been taking high, medium and low doses with/without inhaled LABA respectively and short-acting β 2 agonists (SABA) salbutamol inhaler as needed (prn). The proportion of high doses of fluticasone propionate used by Ethiopian, Ugandan and Kenyan was 45.04%, 30.40% and 2.27% respectively. Utilized medicines proportion across countries are shown in Figure 2 A . At baseline 57.61% patients received inhalational salbutamol prn whereas 93.72% - 97.68% during follow-up. Oral corticosteroids taken at baseline was 39.74% but reduced significantly to 1.55% during follow-up (p<0.001). Montelukast and oral prednisolone utilized at baseline was 16.49%, 8.35% and follow-up and 3.53%, 1.43% respectively. Medicines Adherence Level High, medium, and low medication adherence of participants at baseline: 379 (25.92%), 480 (32.83%), and 603 (41.24%) and overall follow-up adherence level was 1009 (69.04%), 309 (21.15%), and 144 (9.81%) respectively. Of high adherent study participants, despite excellent adherence 34.84% had uncontrolled their asthma. With high adherence but uncontrolled asthma in Ethiopia, Kenya, and Uganda was 35.41%, 43.74%, and 29.19% respectively. High, medium and low adherence level who had three or more worsening asthma attaches were 214 (15.86%), 280 (20.76%) and 333 (24.68%) consecutively. Country wise and each visit medicines adherence level has been shown in Figure 2 B . Place Figure 2 here Asthma control at baseline was 20.71% with a 95% CI (18.67, 22.75), and overall follow-up was 67.61% with a 95% CI (66.66, 68.55). Compared to the baseline, the change brought by the follow-up treatment was 46.90% with a 95% CI (44.41, 49.39) with significant difference (p<0.001). On average at each visit there was a 15.40% increase in asthma control although insignificant in multivariate. Looking into country wise, the proportion of asthma controlled at baseline: Ethiopia, Kenya and Uganda with a 95% CI was 8.12% (5.28, 10.97), 20.62% (16.58, 24.66) and 26.55% (23.43, 29.66) orderly. Overall asthma control during follow-up in Ethiopia, Kenya and Uganda with a 95% CI was 68.23% (66.18, 70.27), 54.79% (52.80, 56.79) and 73.39% (72.18, 74.61) respectively with a significant difference among countries and compared to baseline (p800 μg/day) achieved higher asthma control rates. Participants who were treated with high dose of budesonide-formoterol experienced lower exacerbations. Patients receiving budesonide therapy of 200 - 400 μg, 400 - 800 μg and greater than 800 μg/day had three or more exacerbations rates of 32 (27.59%), 79 (68.10%) and 5 (4.31%) respectively. Participants who were treated with 200–250 μg, 500 μg, and greater than 500 μg/day doses of fluticasone propionate controlled their asthma: 78.05%, 59.53%, and 39.65% correspondingly. Three or more exacerbations before enrollment were discovered to be 916 (60.38%). Three or more exacerbation rate among patients who received low, medium and high doses of inhalational fluticasone propionate found out to be 130 (24.39%), 177 (33.21%), 226 (42.40%) respectively. The following line graph clearly showed the asthma control status at baseline, each follow-up visit, country and overall result. Place Figure 3 here Multivariate analysis revealed that: high level of adherence (p<0.001), lower dose fluticasone propionate (p<0.001) and high budesonide doses plus formoterol (p<0.001) were independently associated with increased in asthma control level. The Ugandan study site demonstrated significant improvements in asthma control (p<001) compared to Ethiopia and Kenya study sites. However, high doses of fluticasone propionate (p<0.001), low adherence level (p<0.001), widower status (p<0.040), and lower doses of budesonide plus formoterol (p<0.001) were all linked to poor predictors for asthma control as depicted in Table 2 . Discussion The study described spirometry, biomarkers, utilized medicines, drug allergy and adherence level. High medicines adherence, low dose fluticasone, and high dose budesonide inhaler were positively associated asthma control. High dose fluticasone, low dose budesonide plus LABA and non-adherence were negatively associated with asthma control. In contrary to others, in our study: sex, marital status, smoking, educational status, spirometry results and high body mass index were not associated as asthma control predictors. Bronchodilator responsiveness measures how much volume and airflow improvements in response to an inhaled short-acting bronchodilator. 29 Delta or changes from post-BD to pre-BD: FEV1, FVC, FEV1/FVC and FEV1% of each study sites were significant between well controlled and uncontrolled asthmatics. These changes were evidenced by other studies. 19, 29 According to ATS and ERS guidelines, a positive spirometry bronchodilator response is confirmed if and only there is a 200 ml increase in FEV1and 12% increase in FVC. This population-based fixed absence and presence BDR criteria has limitations 28 , as a result additionally we used the novel category that revealed 81.51% marked increase in FEV1 of participants with better specificity compared to fixed category BDR of 54.83% of 200 ml and 12% increase in FEV1 and FVC ( Table 1) . This is supported by recent evidence of novel classifications findings of 78.9% BDR. 28 Biomarkers, eosinophilic low or high Th2, FeNO and IgE play pivotal role in asthma diagnosis, pharmacotherapy response and associated clinical decisions. 8, 16, 26 Low-Th2 phenotypes severe asthma characterized by worsening, airway remodeling and poor response to anti-inflammatory glucocorticosteroids. 16, 18 This association might be one factor in non-responders, which was 100% low-Th2 at Ethiopian site. The highest proportion of FeNO >35 part per billion (ppb) was identified in Ethiopian followed by Kenyan. More than 75% of Ugandan study participants had normal range FeNO. The highest normal proportion of Ugandan might be explained by high percentage younger age participants. This might be partly contributed for better asthma control Ugandan site compared to others. The substantial reduction of oral corticosteroids 38.9% utilization during follow-up compared to the baseline 13 was higher than 10.6% change of Italian cohort from baseline study 19 This implies reduction in systemic medication adverse reaction and better improvement during follow-up. 19, 35 Optimal controller medicines utilization with their adherence might be the main attributing factors for controlled asthma in contrast to low adherence and unavailability these medicines at baseline, this is supported by previous findings 3, 7, 13, 20 , mandating due attention for the sustainable availability of controller medicines in the region. Anti-asthma medicines, antibiotics and analgesics associated allergic reactions were self-reported in 120 (39.93%), 114 (37.62%) and 67 (22.44%) respectively. Ugandan site self-reported highest allergic reactions. Antibiotics and non-steroidal anti-inflammatory drugs (NSAID) were known to cause allergic reactions. 36 However, there was scanty reports for anti-asthma medicines allergic reactions 37 although a larger proportion of participants claimed for asthma medicines. This might be an overlapping sensitivity to other allergenic medicines and insight into further investigation. Drug allergy can result in higher morbidity, mortality, delayed treatment commencement, response and lowers patients’ quality of life. This high percentage self-reported allergies would be insightful for prescribers and pharmacists to consider asthma patients. 38 We found 69.04% high, one fifth medium and 10% low medicines adherence rates. This high adherence is higher than 39% pooled result in Africa 9 and other studies elsewhere. 20, 21, 32 But similar with 12 years follow up adherence report conducted in Finland. 39 This higher improvement in medicines adherence level compared to the base line might be the main attributing factor for a 47% change in achievement of asthma control during follow up as medication adherence is critical for asthma control. 40 A significant medication adherence differences among countries, highest in Uganda and lowest in Kenya. Lowest noncompliance probably a contributing factor for lowest asthma control in Kenya. Again, despite high adherence, Kenya recorded the highest rate of uncontrolled asthma, highlighting the need for further research into underlying causes. However, all study sites failed to achieve the minimum required 75-80% adherence level. 40, 41 Overall compared to baseline (20.71%), during follow-up (67.61%; p<0.001), achieved a change in 47% of asthma control ( Table 1) . This finding is higher than earlier studies conducted in Ethiopia 42 , Kenya 11 , Uganda 12 , Middle East and North Africa 43 , Italy 22 , and 35.1% to 61.1% asthma control in United Kingdom. 7, 21 Controller medication use, adherence, GINA guideline follow-up, monthly follow-up, and younger age group in Uganda might be attributing factors for such improvement in asthma control. Place Table 2 here Interestingly, participants treated by low dose fluticasone propionate about 7-fold more likely controlled their asthma with a (95% CI: AOR = 4.26, 9.94) compared with medium dose. Patients received high dose of fluticasone by 81% less likely control their asthma with AOR: 0.19 (95% CI: 0.12, 0.28) in comparison with medium dose. Compared to high dose, the low fluticasone significantly improved asthma control (P< 0.0001). This finding is supported by a randomized controlled trials metanalysis review inhaled corticosteroids evidence that doses of 70–180 μg /d produced 80% of the benefit at 1,000 μg /d, while 100–250 μg /d produced 90%. 35 Low doses of inhaled budesonide plus formoterol and high doses of fluticasone propionate were less likely able to control asthma. Fluticasone propionate or equivalent daily(d) maintenance doses for adults with asthma defined by GINA guidelines using conventional terminology: ”low,” ”medium,” and ”high” doses of inhaled corticosteroids: 100–250 μg, 250–500 μg and > 500 μg respectively. 1, 3 These guidelines recommend increasing the dose of ICS with or without concurrent LABA therapy to achieve optimal control. In contrary to GINA recommendation, our finding revealed low dose of fluticasone showed better treatment outcomes supported by recent findings. 35, 44, 45 We ruled out potential confounding variables namely study site, age, sex, comorbidities, and concomitant medications with their doses as factors influencing the improved asthma outcomes with low-dose fluticasone and found them to have no effect. 46 The pharmacology of fluticasone’s efficacy at lower doses is based on its potency. 47 The link between potency and therapeutic index suggests that increasing potency may enhance the therapeutic index because the two variables are associated. Therefore, considering potency rather than straightforward dose equivalency method, thought as influencing the therapeutic index might be attributing factors for lower dose fluticasone efficacy. 35, 47 Higher doses of fluticasone despite its inability to control asthma majority could be absorbed into systemic circulation. Consequently, might result hoarseness/dysphonia, candidiasis of the mouth and throat, adrenal suppression, growth retardation in children and adolescents, decreased bone mineral density, cataract, glaucoma, hyperglycemia, and contusions 47 even as equivalent adverse effects as 5 mg/day prednisone dose. 44 Remarkably, patients who received high and medium doses of fluticasone experienced three or more exacerbations at the rates of 18.01% and 9.19% respectively compared to low dose receivers. This is in line with recently published evidence in Finland which was 17% of exacerbations with high dose compared to medium dose of inhaled corticosteroids. 44 On the other hand, about 34.84% in our cohort uncontrolled their asthma despite excellent medicines adherence level. This is lower than 70% uncontrolled asthma of highly adherent cohort participants in United Kingdom report. 21 These findings were supported by various researches reported across the globe. 20, 21 This might be explained other factors like disease severity, steroid insensitive, environmental and genetics. 16, 22 Study participants who took high dose of budesonide-formoterol inhaler 3.35 more likely to have better asthma control than low dose takers with a (95% CI:AOR = 2.22, 5.07). Better asthma control with high dose of budesonide-formoterol justified by budesonide low potency. 47 Compared to low medicines adherence study participants those with high adherence controlled their asthma 2 times more likely with a 2.05 (95% CI:1.35, 3.11) supported with studies reported elsewhere. 20, 32, 40, 41 Those who are widowed, and high dose of fluticasone 35, 44 adversely affected asthma control. Nevertheless, a significant percentage (32.39%) of participants still have uncontrolled asthma, demanding further medical intervention. Overall, treatment response variations in terms dose, non-responding despite excellent medication adherence and variations among study sites might dictate the true ground for individualized treatment. In this regard biomarkers have demonstrated encouraging potential in predicting pharmacotherapy responses and optimizing treatments approaches across a range of populations based pharmacokinetic and pharmacodynamic models 48 . To sum up, phenotypic differences of clinical significance in pharmacotherapy have been explained by pharmacogenetics investigations of causal relationships between genotypes and medication response. 15, 18 The ”five rights” administering appropriate medicines to appropriate patient at appropriate time, in the appropriate dose, and via appropriate route of administration are the cornerstones of the framework for good clinical outcome. Therefore, considering of precision medicine is necessity, which accounts the patient’s genetics, environmental, lifestyle, and medical history 48 . Limitations, post bronchodilator for denominator used to calculate spirometry dynamics due to lack of validated predicted value in Africans. Non-adherence predicting factors were not identified. We didn’t investigate pharmacogenomics determinants. The main strengths were prospective longitudinal cohort with multi country. We employed advanced statistical model to accommodate repeated measurement of study variables during follow-up. The study’s generalizability was boosted by the fact that it was multicounty, real-world and used validated instruments to measure results. Conclusion : We demonstrated remarkable asthma control during follow-up compared to baseline with variability among countries. High medicines adherence, low dose fluticasone, high dose budesonide inhaler and Uganda study site were associated with high asthma control. High dose fluticasone, low dose budesonide + LABA, non-adherence and being widowed were negatively associated factors with asthma control. Our findings suggest reconsidering inhaled corticosteroid doses. Importantly, despite the standard treatment of care during follow-up and high medicines adherence a substantial percentage of patients still uncontrolled their asthma. Therefore, it is the right time to consider precision medicine which accounts for an individual’s genetics profile, environmental, and lifestyle. Abbreviations and acronyms used ACQ: Asthma control questionnaire ASAP: African Severe Asthma Project AOD: Adjusted Odds Ratio ATS: American Thoracic Society BHQ: Bronchial hyperresponsiveness questionnaire CI: Confidence interval ERS: European Respiratory Society FENO: Fraction of exhaled nitric oxide FEV: Forced expiratory volume FEV1: Forced expiratory volume in 1 second GINA: Global Initiative for Asthma ICS: Inhaled corticosteroid LABA: Long-acting β2-agonist SABA: Short-acting β2-agonist WHO: World Health Organization Acknowledgment Authors are grateful to every study participant who agreed to take part in ASAP. We want to thank all of the physicians who recruited and followed up with patients ASAP for their unwavering commitment. We also thank the data quality assurance team and all of the data officers and the data manager. Author Contributions KAG, BK, GY, AM and JC conceptualized the study. KAG, NB, BK, GY, SAM, AB, JC and TM design the study. KAG, LM and MW cleaned the data. KAG, NB, SAM, JC, GY, BK, AB, LM and TM analyzed the data. Data curation, all authors. KAG drafted the original manuscript and finalized with substantial input from all authors. Each author critically evaluated the manuscript, approved the final version for publication, selected the journal to which the article was submitted, and agreed to take responsibility for all elements of the work and made a substantial contribution to the published work. Funding acquisition BK, GY, AB, JC and SAM. Funding: GSK Africa Non-Communicable Disease Open Lab project funding (Project number: 8019) provided funding for the investigation. The funder did not participate in the study design, data collection, analysis, or publication decision. Final published content will be also under the authors’ control. 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Am J Respir Crit Care Med. 2020;201(12):1480-7.46. Thomas M, von Ziegenweidt J, Lee AJ, Price D. High-dose inhaled corticosteroids versus add-on long-acting beta-agonists in asthma: an observational study. J Allergy Clin Immunol. 2009;123(1):116-21.47. Daley-Yates PT. Inhaled corticosteroids: potency, dose equivalence and therapeutic index. Br J Clin Pharmacol. 2015;80(3):372-80.48. Marques L, Costa B, Pereira M, Silva A, Santos J, Saldanha L, et al. Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare. Pharmaceutics. 2024;16(3). Supplementary Material File (figure_1.docx) Download 291.92 KB File (figure_2.docx) Download 156.55 KB File (figure_3.docx) Download 45.00 KB File (table_1.docx) Download 22.99 KB File (table_2.docx) Download 20.12 KB Information & Authors Information Version history V1 Version 1 17 June 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Kefyalew Getahun University of Gondar College of Medicine and Health Sciences View all articles by this author Nega Birhane University of Gondar Institute of Biotechnology View all articles by this author Winters Muttamba Makerere University Lung Institute View all articles by this author Levicatus Mugenyi Makerere University Lung Institute View all articles by this author Jeremiah Chakaya Mount Kenya University College of Health Sciences View all articles by this author Amsalu Bekele Addis Ababa University School of Medicine View all articles by this author Solomon Mequanente Abay Addis Ababa University College of Health Sciences View all articles by this author Tesfaye B. Mersha 0000-0002-9189-8447 University of Cincinnati Department of Pediatrics View all articles by this author Getnet Yimer University of Pennsylvania Perelman School of Medicine View all articles by this author Bruce J. Kirenga [email protected] Makerere University Lung Institute View all articles by this author Metrics & Citations Metrics Article Usage 179 views 92 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Kefyalew Getahun, Nega Birhane, Winters Muttamba, et al. Pharmacotherapy and Determinants of Asthma Control in Eastern Africa. Authorea . 17 June 2025. DOI: https://doi.org/10.22541/au.175016327.71023857/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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