Introduction
Anticholinergic drugs are commonly prescribed among patients worldwide, despite their potential side effects. These side effects range from classical manifestations such as dry mouth, blurred vision, and constipation to more advanced adverse effects such as confusion, delirium, cognitive impairment, dementia, and increased falls and mortality risk ( Tune, 2001 ). Elderly patients are at high risk of developing drug-related adverse effects due to the fact that with aging, more chronic conditions develop, necessitating the administration of more medications to control these problems (polypharmacy) and stabilize their disease condition ( Canio, 2022 , Choi et al., 2023 ).
Anticholinergic side effects incidence and severity are generally augmented by administering more than one drug with anticholinergic effects at the same time, which can be a problem for elderly patients who are often on multiple medications ( Salahudeen et al., 2015b , Tristancho-Perez et al., 2021 , Villalba-Moreno et al., 2018 ) elderly patients are more prone to anticholinergic adverse events, especially those affecting the central nervous system, owing to an elevated blood–brain barrier permeability of these medications ( Campbell et al., 2009 , Chancellor et al., 2012 ). These side effects impact geriatrics more than other age groups because of aging-associated shortage in cholinergic signaling centrally ( Sultzer et al., 2022 ).
In addition, the changes in both pharmacokinetics and pharmacodynamic parameters encountered in elderly patients will expose them to more chances of side effects, especially life-threatening adverse events ( Mangoni and Jackson, 2004 , Sumpio et al., 2016 , West et al., 2013 ).
Management of cancer and terminally ill patients is generally complex and time-consuming. Treatment of patients with cancer depends mainly on various treatment modalities, including chemotherapy protocols, where the use of different anticancer drugs with different mechanisms and adverse effects profiles is compulsory ( Sumpio et al., 2016 ).
The current number of elderly patients living with cancer in Jordan is increasing due to increased life expectancy among the population over the past years ( Al-Azayzih et al., 2020 ), and in addition to a noticed increase in the prevalence of various tumors in the same group ( Abdel-Razeq et al., 2022 , Abdel-Razeq et al., 2020 ). In addition to cancer, geriatric patients often have other types of chronic conditions and comorbidities, such as cardiovascular, psychological, neurological, diabetes, and other health problems, making the treatment scenario in these patients highly complicated ( Williams et al., 2016 ).
Research aim
Evaluating the anticholinergic burden and inappropriate prescribing behavior among the elderly population is a priority. Therefore, the aim of our research is to assess the prevalence of anticholinergic prescribing, cumulative anticholinergic burden of medication utilized, and to identify the major predictors associated with anticholinergic prescribing in geriatric population surviving cancer. This study should provide a basis for future prescribing recommendations to eliminate the serious side effects that might result from taking medications with anticholinergic characteristics.
Methodology
Study design and Setting
This retrospective cross-sectional study was conducted on elderly patients (Age in years ≥ 65) who were diagnosed with either solid or hematological cancers and admitted to the adult oncology department at King Abdullah University Hospital (KAUH) during the period between January 1st, 2019, and January 1st, 2022), KAUH is considered as the main referral center for cancer patients in the North of Jordan.
Sample size Calculations
Sample size was calculated according to Krejcie and Morgan formula ( Krejcie and Morgan, 1970 ) to obtain 50% population proportion (to achieve the highest number of subjects) and a 95% confidence interval with a margin of error of 5%. A total number of 384 subjects or more were required to meet the sample size calculation of the predetermined parameters values.
Patients characteristics and data Collection
A total of 420 patients were included in the study, electronic medical and clinical charts from the KAUH electronic medical system for specific patients were assessed retrospectively for further data extraction and analysis. Patients’ characteristics such as gender, average age, and frequency of specific cancer were collected. The frequency of drugs with anticholinergic potency was evaluated and calculated based on the list reported by CRIDECO Anticholinergic Load Scale (CALS) score ( Ramos et al., 2022 ). CALS was developed by group of researchers from Spain after running an intensive systematic review and comparing list of anticholinergic drugs included in the previous seven scores including Anticholinergic drug scale ( Carnahan et al., 2006 ), Anticholinergic Risk Scale ( Rudolph et al., 2008 ), Anticholinergic Cognitive Burden Scale ( Campbell et al., 2009 ), Duran Scale ( Duran et al., 2013 ), Salahudeen Scale ( Salahudeen et al., 2015a ), German Anticholinergic Scales ( Kiesel et al., 2018 ), and Korean Anticholinergic Activity Scale ( Jun et al., 2019 ). CALS list includes a total of 217 drugs with anticholinergic effects, which were further classified into three categories based on their anticholinergic potency: drugs with low anticholinergic potency (score = 1) and total of 125 medications in this category, drugs with medium anticholinergic potency (score = 2) with 28 drugs in medium potency category, and drugs with high anticholinergic potency (score = 3) with 62 drugs in the high potency category. The drugs with anticholinergic properties administered to patients were also categorized according to the Anatomical Therapeutic Chemical (ATC) system ( WHO ). The ATC data were represented as the frequency of the total number of drugs belonging to each individualized ATC category. Finally, the cumulative anticholinergic burden was counted for each patient utilizing the updated CALS score. Briefly, the burden score for each drug taken by each patient was added together to obtain the final cumulative anticholinergic score (0, 1, 2, 3, 4, or ≥ 5). A cumulative score of 3 or more was considered a high burden score.
Statistical analysis
The data was entered and analyzed using Microsoft 365 Excel. Descriptive statistics were performed to describe the elderly cancer patients’ characteristics. Both continuous and categorical parameters were presented as a sum, average ± standard deviation, median (IQR) and frequency, respectively. Multivariable logistic regression module was applied to examine potential predictors associated with anticholinergic risk burden increase. Statistically significant difference was assumed at P value of less than 0.05.
Results
The results of the study indicate that a total of 420 geriatric cancer patients were analyzed, with 207 (49.3%) being female. The average age of the study sample was 72.95 (SD = 7.33) years. Median of total medications prescribed was 10 (IQR = 7), while median for anticholinergic medications was 3 (IQR = 4). Polypharmacy index of ≥ 5 drugs was present in 362 patients (86.2%). Breast cancer (16.2%), colorectal (13.1%), and lung cancer (12.86%) were found to be the most common cancers among the study population ( Table 1 ).
Table 1
Patients Characteristics.
* Others: (include, esophageal, brain, gall gladder, skin, bone and connective tissue, peritoneal mesothelioma, parotid gland, adrenal gland, thyroid, thymus, submandibular gland, urethra, tongue, nasopharynx, …. etc.).
| Variable | Category | N ± SD Or Median (IQR) | Percentage (%) |
| Gender | Male | 213 | 50.7% |
| Female | 207 | 49.3% | |
| Both | 420 | 100% | |
| Average Age (years) | 72.95 (SD = 7.33) | ||
| Median (IQR) of Total Medications Prescribed | 10 (7) | ||
| Median (IQR) of Anticholinergic Medications Prescribed | 3 (4) | ||
| Patients who have Polypharmacy (≥5 Prescribed Medications) | 362 | 86.2% | |
| Types of solid and hematological cancers | Brest Cancer | 68 | 16.20% |
| Colorectal | 55 | 13.10% | |
| Lung | 54 | 12.86% | |
| Bladder | 40 | 9.52% | |
| Prostate | 25 | 5.60% | |
| stomach | 22 | 5.23% | |
| Endometrial | 19 | 4.50% | |
| Lymphoma | 18 | 4.28% | |
| Leukemia | 17 | 4.07% | |
| Multiple Myeloma | 13 | 3.10% | |
| Pancreatic | 13 | 3.10% | |
| Ovary | 12 | 2.86% | |
| Liver | 12 | 2.86% | |
| Kidney | 10 | 2.38% | |
| * Others | 42 | 10% |
The study found that a total of 33 medications with anticholinergic effects were administered to patients. Metoclopramide was the most frequently administered medication with anticholinergic properties, with a frequency (n) of 150 (42.4%), followed by furosemide (n = 129 (36.4%)), and tramadol (n = 85 (24.0%)) ( Table 2 ). Furthermore, results indicated that percent of patients with at least 1 anticholinergic was 84.3%, Also, the pie chart ( Fig. 1 ) showed that patient’s number, n (%) who were taking specific number of anticholinergic medications (1,2,3,4, and ≥ 5) were as follow: 109 (30.8%), 80 (22.6%), 72 (20.4%), 49 (13.8%), and 44 (12.4%); respectively. Additionally, in terms of medication categories, alimentary tract medicines (Frequency = 340) were the most frequently administered anticholinergic medicines, followed by drugs that work on the nervous system (Frequency = 235), cardiovascular system (Frequency = 203), respiratory tract and antiallergic medicines (Frequency = 141), anti-infective medicines for systemic use (Frequency = 17), and musculoskeletal system (Frequency = 7) ( Fig. 2 ).
Table 2
Most common anticholinergic agents prescribed for patients.
*Codeine was in combination with Paracetamol (Paracetamol 500 mg + Codeine Phosphate 10 mg) Tablet. *Orphenadrine was in combination with Paracetamol (Orphenadrine 35 mg + Paracetamol 450 mg) Tablet. *Pseudoephedrine was in cough mixture (Guaifenesin 100 mg + Pseudoephedrine 20 mg).
| Drug | Total Anticholinergic Drug Users N = 354 (% of total N) | Anticholinergic Potency (Scale 1 – 3) |
| Metoclopramide | 150 (42.4%) | 1 |
| Furosemide | 129 (36.4%) | 1 |
| Tramadol | 85 (24.0%) | 2 |
| Bisacodyl | 60 (16.9%) | 1 |
| Metoprolol | 55 (15.5%) | 1 |
| Chlorpheniramine | 53 (15.0%) | 3 |
| Metformin | 50 (14.1%) | 1 |
| Hydrocortisone | 50 (14.1%) | 1 |
| Alprazolam | 41 (11.6%) | 1 |
| Loperamide | 37 (10.5%) | 1 |
| Ranitidine | 31 (8.8%) | 2 |
| *Codeine | 29 (8.2%) | 1 |
| Fentanyl | 29 (8.2%) | 1 |
| Prednisolone | 25 (7.1%) | 1 |
| Olanzapine | 15 (4.2%) | 2 |
| Vancomycin | 13 (3.7%) | 1 |
| *Pseudoephedrine | 11 (3.1%) | 1 |
| Warfarin | 10 (2.8%) | 1 |
| Nifedipine | 9 (2.5%) | 1 |
| Mirtazapine | 8 (2.3%) | 1 |
| *Orphenadrine | 7 (2.0%) | 3 |
| Domperidone | 7 (2.0%) | 1 |
| Hyoscyamine or Hyoscine | 7 (2.0%) | 3 |
| Quetiapine | 6 (1.7%) | 2 |
| Carbamazepine | 6 (1.7%) | 2 |
| Valproic Acid | 4 (1.1%) | 1 |
| Amitriptyline | 4 (1.1%) | 3 |
| Gentamycin/ Gentamicin | 4 (1.1%) | 1 |
| Citalopram | 4 (1.1%) | 1 |
| Escitalopram | 3 (0.8%) | 1 |
| Theophylline | 2 (0.6%) | 1 |
| Famotidine | 2 (0.6%) | 1 |
| Amantadine | 1 (0.3%) | 2 |
The study also aimed to determine the cumulative anticholinergic burden score in patients. The results revealed that 354 (84.3%) patients were prescribed at least one anticholinergic medication, with 97 patients having a cumulative score of 1, 60 patients having a score of 2, 57 patients having a score of 3, 36 patients having a score of 4, and 104 patients having a cumulative score of 5 or more. The highest cumulative score reported among patients was 13 ( Table 3 ).
Table 3
Anticholinergic Burden Score for Patients (N = 420).
| Cumulative Anticholinergic Burden Score | Number of Patients with Anticholinergic Score |
| 0 | 66 |
| 1 | 97 |
| 2 | 60 |
| 3 | 57 |
| 4 | 36 |
| ≥5 | 104 |
| Total | 420 |
Investigating the possible variables which might be associated with increased the anticholinergic burden among older cancer patients. This study evaluated polypharmacy, age, gender, and type of cancer as predictive variables for anticholinergic burden score increment. Only polypharmacy was associated significantly with more odds of higher anticholinergic burden score ( Table 4 ).
Table 4
Multivariable logistic regression: dependent variable is anticholinergic drugs burden score.
* P < 0.05 was considered statistically significant. # Solid or Hematological Cancers.
| Variable | OR (95%CI) | P-value |
| Polypharmacy | 1.532 (1.378–1.703) | * <0.001 |
| Age | 1.008 (0.963–1.054) | 0.740 |
| Gender (Male) | 1.731 (0.899–3.333) | 0.101 |
| # Type of cancer | 1.267 (0.462–3.475) | 0.646 |
Overall, these findings suggest that a substantial proportion of geriatric cancer patients were prescribed medications with anticholinergic properties, which can potentially lead to an increased risk of adverse events. The identification and monitoring of anticholinergic burden in this vulnerable population may help to optimize their medication regimens and improve their overall quality of life.
Discussion
This study is the first to evaluate the prevalence and prescribing attitude, as well as identifying the cumulative anticholinergic burden of medications with anticholinergic effects among elderly cancer patients in Jordan.
Results of this study showed that 84.3% (n = 354 out of 420) of the study patients had been exposed to at least one anticholinergic drug with different anticholinergic potency. Surprisingly, our data found that around one-quarter of the patients had a cumulative burden of ≥5 (n = 104 out of 420) where the highest cumulative score reported equal to 13. Compared to previous reports, our results indicated an elevated prescribing and administration of drugs with anticholinergic burden in our study subjects. Recent studies from all around the world showed significant variations in prevalence rates of anticholinergic effects exposure. ( Cebron Lipovec et al., 2020 , Cross et al., 2016 , Havnes et al., 2023 , Mantri et al., 2019 , Mayer et al., 2017 , Salahudeen et al., 2015b , Tristancho-Perez et al., 2021 ). This significant difference in our study regarding anticholinergic burden prevalence could be due to many factors, including first, the utilization of a newer anticholinergic burden scale (CALS) where the list of potential anticholinergic drugs contains 217 drugs ( Ramos et al., 2022 ). In contrary to other scales where the list of drugs has between (49–195) medications ( Carnahan et al., 2006 , Duran et al., 2013 , Rudolph et al., 2008 , Salahudeen et al., 2015a ). Also, polypharmacy and the complex nature of treatment modalities in elderly cancer patients might signify the opportunities for these drugs prescribing ( Canio, 2022 , Sumpio et al., 2016 ).
Different drugs were identified to carry anticholinergic burden and were taken by our study patients. Metoclopramide was at the top of the list, followed by furosemide and tramadol. While it is common to see metoclopramide prescribed for cancer patients to control their breakthrough nausea and vomiting, it is still recommended to minimize the exposure of metoclopramide by prescribing appropriate pre-chemotherapy medications for nausea and vomiting ( Davis et al., 2021 ). On the other hand, opioid analgesics (tramadol) and other psychotropic medications such as alprazolam, olanzapine, quetiapine, mirtazapine, valproic acid, amitriptyline, and citalopram and escitalopram were commonly prescribed in this study with high agreement to previous reports outcomes indicated that opioids analgesics and other psychotropic drugs are highly prevalent and represent a major source of anticholinergic burden in both geriatrics and cancer populations( Cebron Lipovec et al., 2020 , Gorup et al., 2018 , Lopez-Alvarez et al., 2019 ).
Interestingly, alimentary tract medicines according to ATC classification followed by drugs that work on the central nervous system and cardiovascular system were the most common medicines prescribed among study subjects. For example, ranitidine was frequent in 31 patients carrying an anticholinergic potency score equal to 2. According to a randomized clinical trial, proton pump inhibitors are considered much safer medications to replace ranitidine prescribing, knowing that PPI carries no known anticholinergic burden effects when used either chronically or as needed by elderly patients ( Hansen et al., 2006 ). Chlorpheniramine, a first-generation antihistamine with a definite anticholinergic burden (score = 3), was encountered in 53 patients, representing 14.9% of the total number of patients. While it is highly discouraged to use first-generation antihistamines in the senior population, second-generation antihistamines such as loratadine and fexofenadine (anticholinergic potency score = 1) provide a better and safer alternative to these patients, carrying minimal anticholinergic activity compared to chlorpheniramine ( Ramos et al., 2022 ).
According to several studies, a cumulative anticholinergic burden ≥3 will render the patients at high risk of falls, cognitive impairments, delirium, and dementia ( Lisibach et al., 2021 ). Unfortunately, our study revealed that around 25% of the patients scored a cumulative burden risk of 5 or more. Polypharmacy was reported in several studies to be associated with rise in the cumulative anticholinergic burden, thus, growing risk of falls and cognitive impairment among elderly patients. ( Bourrel et al., 2020 , Okudur et al., 2021 ). Our results were in agreement with those reports suggesting a greater correlation between polypharmacy and higher cumulative anticholinergic burden and risk of falls and other adverse events in elderly compared to age and comorbidities ( Wong et al., 2023 ).
Study limitations
This study was conducted retrospectively with cross-sectional design. Hence, can’t address the cause and effects associations. Also, due to the retrospective design, data were extracted from the electronic medical charts of the patients, thus, reporting actual adverse events related to anticholinergic drugs action was not feasible. The study was conducted utilizing patients from only one cancer hospital (KAUH) in Jordan. Therefore, the extrapolation of the study findings might be affected to little extent, due to different reasons, first, the KAUH does serve large and highly populated geographical area in Jordan. Second, KAUH is one of the major hospitals in Jordan which specialized in treating different types of solid and hematological diseases.
Conclusion
The prevalence of drugs carrying anticholinergic burden risk was high among elderly cancer patients. The most commonly prescribed medications associated with anticholinergic risk were drugs that work on the alimentary tract, followed by those that affect the central nervous system and cardiovascular system. The cumulative anticholinergic burden, which is associated with a risk of serious adverse events, was found to exist in almost half of the patients and polypharmacy was the mainly predictor for cumulative anticholinergic burden increment. There is no doubt that there is a crucial need to adopt preventative prescribing and prescribing measures to minimize the risks associated with the use of drugs with anticholinergic burden in geriatric cancer patients.
Ethical approval
Institutional ethical approvals were obtained as per institutional research board (IRB) requirements at KAUH (King Abullah University Hospital), IRB Approval number (KA 61/147/2022). Data confidentiality was ensured by the authors throughout the whole process of study period and under the responsibility of the corresponding author according to IRB regulations. Patients’ identification numbers were replaced by serial numerical numbers.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement and Funding
This research has received approvals from deanship of scientific research at Jordan University of Science and Technology (Approval # 33-2022) and Institutional Review Board at KAUH. No financial fund was received to conduct this research.
Footnotes
Peer review under responsibility of King Saud University.
References
Abdel-Razeq H., Mansour A., Bater R. Trends, patterns, and treatment outcomes of cancer among older patients in Jordan: a retrospective analysis of national cancer registry and institutional outcome data. JCO Glob. Oncol. 2020;6:745–751. doi: 10.1200/GO.20.00044.
Abdel-Razeq H., Abu Rous F., Abuhijla F., Abdel-Razeq N., Edaily S. Breast cancer in geriatric patients: current landscape and future prospects. Clin. Interv. Aging. 2022;17:1445–1460. doi: 10.2147/CIA.S365497.
Al-Azayzih A., Al-Azzam S.I., Alzoubi K.H., Jarab A.S., Kharaba Z., Al-Rifai R.H., Alnajjar M.S. Nonsteroidal anti-inflammatory drugs utilization patterns and risk of adverse events due to drug-drug interactions among elderly patients: a study from Jordan. Saudi Pharm. J. 2020;28(4):504–508. doi: 10.1016/j.jsps.2020.03.001.
Bourrel C., Zacarin A., Rousseau V., Montastruc J.L., Bagheri H. Are potentially inappropriate and anticholinergic medications being prescribed for institutionalized elderly subjects? Fundam. Clin. Pharmacol. 2020;34(6):743–748. doi: 10.1111/fcp.12560.
Campbell N., Boustani M., Limbil T., Ott C., Fox C., Maidment I., Gulati R. The cognitive impact of anticholinergics: a clinical review. Clin. Interv. Aging. 2009;4:225–233. doi: 10.2147/cia.s5358.
Canio W.C. Polypharmacy in older adults. Clin. Geriatr. Med. 2022;38(4):621–625. doi: 10.1016/j.cger.2022.05.004.
Carnahan R.M., Lund B.C., Perry P.J., Pollock B.G., Culp K.R. The Anticholinergic Drug Scale as a measure of drug-related anticholinergic burden: associations with serum anticholinergic activity. J. Clin. Pharmacol. 2006;46(12):1481–1486. doi: 10.1177/0091270006292126.
Cebron Lipovec N., Jazbar J., Kos M. Anticholinergic burden in children, adults and older adults in Slovenia: A nationwide database study. Sci. Rep. 2020;10(1) doi: 10.1038/s41598-020-65989-9.
Chancellor M.B., Staskin D.R., Kay G.G., Sandage B.W., Oefelein M.G., Tsao J.W. Blood-brain barrier permeation and efflux exclusion of anticholinergics used in the treatment of overactive bladder. Drugs Aging. 2012;29(4):259–273. doi: 10.2165/11597530-000000000-00000.
Choi D.W., Kang H., Zhang H.S., Jhang H., Jeong W., Park S. Association of polypharmacy with all-cause mortality and adverse events among elderly colorectal cancer survivors. Cancer. 2023 doi: 10.1002/cncr.34813.
Cross A.J., George J., Woodward M.C., Ames D., Brodaty H., Ilomaki J., Elliott R.A. Potentially inappropriate medications and anticholinergic burden in older people attending memory clinics in Australia. Drugs Aging. 2016;33(1):37–44. doi: 10.1007/s40266-015-0332-3.
Davis M., Hui D., Davies A., Ripamonti C., Capela A., DeFeo G., Bruera E. MASCC antiemetics in advanced cancer updated guideline. Support Care Cancer. 2021;29(12):8097–8107. doi: 10.1007/s00520-021-06437-w.
Duran C.E., Azermai M., Vander Stichele R. Systematic review of anticholinergic risk scales in older adults. Response to letter of the editor. Eur. J. Clin. Pharmacol. 2013;69(9) doi: 10.1007/s00228-013-1536-2.
Gorup E., Rifel J., Petek Ster M. Anticholinergic burden and most common anticholinergic-acting medicines in older general practice patients. Zdr. Varst. 2018;57(3):140–147. doi: 10.2478/sjph-2018-0018.
Hansen A.N., Bergheim R., Fagertun H., Lund H., Wiklund I., Moum B. Long-term management of patients with symptoms of gastro-oesophageal reflux disease – a Norwegian randomised prospective study comparing the effects of esomeprazole and ranitidine treatment strategies on health-related quality of life in a general practitioners setting. Int. J. Clin. Pract. 2006;60(1):15–22. doi: 10.1111/j.1368-5031.2006.00768.x.
Havnes K., Svendsen K., Johansen J.S., Granas A.G., Garcia B.H., Halvorsen K.H. Is anticholinergic and sedative drug burden associated with postdischarge institutionalization in community-dwelling older patients acutely admitted to hospital? A Norwegian registry-based study. Pharmacoepidemiol. Drug Saf. 2023;32(6):607–616. doi: 10.1002/pds.5590.
Jun K., Hwang S., Ah Y.M., Suh Y., Lee J.Y. Development of an Anticholinergic Burden Scale specific for Korean older adults. Geriatr. Gerontol. Int. 2019;19(7):628–634. doi: 10.1111/ggi.13680.
Kiesel E.K., Hopf Y.M., Drey M. An anticholinergic burden score for German prescribers: score development. BMC Geriatr. 2018;18(1) doi: 10.1186/s12877-018-0929-6.
Krejcie R.V., Morgan D.W. Determining sample size for research activities. Educ. Psychol. Meas. 1970;30(3):607–610. doi: 10.1177/001316447003000.
Lisibach A., Benelli V., Ceppi M.G., Waldner-Knogler K., Csajka C., Lutters M. Quality of anticholinergic burden scales and their impact on clinical outcomes: a systematic review. Eur. J. Clin. Pharmacol. 2021;77(2):147–162. doi: 10.1007/s00228-020-02994-x.
Lopez-Alvarez J., Sevilla-Llewellyn-Jones J., Aguera-Ortiz L. Anticholinergic drugs in geriatric psychopharmacology. Front. Neurosci. 2019;13 doi: 10.3389/fnins.2019.01309.
Mangoni A.A., Jackson S.H. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br. J. Clin. Pharmacol. 2004;57(1):6–14. doi: 10.1046/j.1365-2125.2003.02007.x.
Mantri S., Fullard M., Gray S.L., Weintraub D., Hubbard R.A., Hennessy S., Willis A.W. Patterns of dementia treatment and frank prescribing errors in older adults with Parkinson disease. JAMA Neurol. 2019;76(1):41–49. doi: 10.1001/jamaneurol.2018.2820.
Mayer T., Meid A.D., Saum K.U., Brenner H., Schottker B., Seidling H.M., Haefeli W.E. Comparison of nine instruments to calculate anticholinergic load in a large cohort of older outpatients: association with cognitive and functional decline, falls, and use of laxatives. Am. J. Geriatr. Psychiatry. 2017;25(5):531–540. doi: 10.1016/j.jagp.2017.01.009.
Okudur S.K., Dokuzlar O., Aydin A.E., Kocyigit S.E., Soysal P., Isik A.T. The evaluation of relationship between polypharmacy and anticholinergic burden scales. North Clin. Istanb. 2021;8(2):139–144. doi: 10.14744/nci.2020.17136.
Ramos H., Moreno L., Perez-Tur J., Chafer-Pericas C., Garcia-Lluch G., Pardo J. CRIDECO anticholinergic load scale: an updated anticholinergic burden scale. comparison with the ACB scale in spanish individuals with subjective memory complaints. J. Pers. Med. 2022;12(2) doi: 10.3390/jpm12020207.
Rudolph J.L., Salow M.J., Angelini M.C., McGlinchey R.E. The anticholinergic risk scale and anticholinergic adverse effects in older persons. Arch. Intern. Med. 2008;168(5):508–513. doi: 10.1001/archinternmed.2007.106.
Salahudeen M.S., Duffull S.B., Nishtala P.S. Anticholinergic burden quantified by anticholinergic risk scales and adverse outcomes in older people: a systematic review. BMC Geriatr. 2015;15 doi: 10.1186/s12877-015-0029-9.
Salahudeen M.S., Hilmer S.N., Nishtala P.S. Comparison of anticholinergic risk scales and associations with adverse health outcomes in older people. J. Am. Geriatr. Soc. 2015;63(1):85–90. doi: 10.1111/jgs.13206.
Sultzer D.L., Lim A.C., Gordon H.L., Yarns B.C., Melrose R.J. Cholinergic receptor binding in unimpaired older adults, mild cognitive impairment, and Alzheimer's disease dementia. Alzheimers Res. Ther. 2022;14(1) doi: 10.1186/s13195-021-00954-w.
Sumpio C., Knobf M.T., Jeon S. Treatment complexity: a description of chemotherapy and supportive care treatment visits in patients with advanced-stage cancer diagnoses. Support Care Cancer. 2016;24(1):285–293. doi: 10.1007/s00520-015-2775-9.
Tristancho-Perez A., Villalba-Moreno A., Santos-Rubio M.D., Lopez-Malo M.D., Santos-Ramos B., Sanchez-Fidalgo S. Anticholinergic exposure in elderly complex chronic patients: a cross-sectional study. Curr. Pharm. Des. 2021;27(40):4186–4194. doi: 10.2174/1381612827666210830164054.
Tune L.E. Anticholinergic effects of medication in elderly patients. J. Clin. Psychiatry. 2001;62(Suppl 21):11–14. https://www.ncbi.nlm.nih.gov/pubmed/11584981
Villalba-Moreno A.M., Alfaro-Lara E.R., Rodriguez-Perez A., Banez-Toro D., Sanchez-Fidalgo S., Perez-Guerrero M.C., Nieto-Martin M.D. Association between drug burden index and functional and cognitive function in patients with multimorbidity. Curr. Pharm. Des. 2018;24(28):3384–3391. doi: 10.2174/1381612824666180327154239.
West T., Pruchnicki M.C., Porter K., Emptage R. Evaluation of anticholinergic burden of medications in older adults. J. Am. Pharm. Assoc. 2013;53(5):496–504. doi: 10.1331/JAPhA.2013.12138.
WHO. World Health Organization. Anatomical Therapeutic Chemical (ATC) classification system. Retrieved from https://www.who.int/standards/classifications/other-classifications/the-anatomical-therapeutic-chemical-classification-system-with-defined-daily-doses .
Williams G.R., Mackenzie A., Magnuson A., Olin R., Chapman A., Mohile S., Holmes H. Comorbidity in older adults with cancer. J. Geriatr. Oncol. 2016;7(4):249–257. doi: 10.1016/j.jgo.2015.12.002.
Wong H.L., Weaver C., Marsh L., Mon K.O., Dapito J.M., Amin F.R., Missouris C.G. Polypharmacy and cumulative anticholinergic burden in older adults hospitalized with fall. Aging Med. (Milton) 2023;6(2):116–123. doi: 10.1002/agm2.12250.