Anticholinergic burden for prediction of cognitive decline or neuropsychiatric symptoms in older adults with mild cognitive impairment or dementia

Acknowledgements We would like to thank Dr Kate Wang, Dr Andrew Stafford, Ms Catherine Hofstetter, and Dr Joanna Damen for their helpful peer review comments on this protocol.Peer reviewedPublisher PD

Anticholinergic burden for prediction of cognitive decline or neuropsychiatric symptoms in older adults with mild cognitive impairment or dementia

Background: Medications with anticholinergic properties are commonly prescribed to older adults with a pre‐existing diagnosis of dementia or cognitive impairment. The cumulative anticholinergic effect of all the medications a person takes is referred to as the anticholinergic burden because of its potential to cause adverse effects. It is possible that a high anticholinergic burden may be a risk factor for further cognitive decline or neuropsychiatric disturbances in people with dementia. Neuropsychiatric disturbances are the most frequent complication of dementia that require hospitalisation, accounting for almost half of admissions; hence, identification of modifiable prognostic factors for these outcomes is crucial. There are various scales available to measure anticholinergic burden but agreement between them is often poor. Objectives: Our primary objective was to assess whether anticholinergic burden, as defined at the level of each individual scale, was a prognostic factor for further cognitive decline or neuropsychiatric disturbances in older adults with pre‐existing diagnoses of dementia or cognitive impairment. Our secondary objective was to investigate whether anticholinergic burden was a prognostic factor for other adverse clinical outcomes, including mortality, impaired physical function, and institutionalisation. Search methods: We searched these databases from inception to 29 November 2021: MEDLINE OvidSP, Embase OvidSP, PsycINFO OvidSP, CINAHL EBSCOhost, and ISI Web of Science Core Collection on ISI Web of Science. Selection criteria: We included prospective and retrospective longitudinal cohort and case‐control observational studies, with a minimum of one‐month follow‐up, which examined the association between an anticholinergic burden measurement scale and the above stated adverse clinical outcomes, in older adults with pre‐existing diagnoses of dementia or cognitive impairment. Data collection and analysis: Two review authors independently assessed studies for inclusion, and undertook data extraction, risk of bias assessment, and GRADE assessment. We summarised risk associations between anticholinergic burden and all clinical outcomes in a narrative fashion. We also evaluated the risk association between anticholinergic burden and mortality using a random‐effects meta‐analysis. We established adjusted pooled rates for the anticholinergic cognitive burden (ACB) scale; then, as an exploratory analysis, established pooled rates on the prespecified association across scales. Main results: We identified 18 studies that met our inclusion criteria (102,684 older adults). Anticholinergic burden was measured using five distinct measurement scales: 12 studies used the ACB scale; 3 studies used the Anticholinergic Risk Scale (ARS); 1 study used the Anticholinergic Drug Scale (ADS); 1 study used the Anticholinergic Effect on Cognition (AEC) Scale; and 2 studies used a list developed by Tune and Egeli. Risk associations between anticholinergic burden and adverse clinical outcomes were highly heterogenous. Four out of 10 (40%) studies reported a significantly increased risk of greater long‐term cognitive decline for participants with an anticholinergic burden compared to participants with no or minimal anticholinergic burden. No studies investigated neuropsychiatric disturbance outcomes. One out of four studies (25%) reported a significant association with reduced physical function for participants with an anticholinergic burden versus participants with no or minimal anticholinergic burden. No study (out of one investigating study) reported a significant association between anticholinergic burden and risk of institutionalisation. Six out of 10 studies (60%) found a significantly increased risk of mortality for those with an anticholinergic burden compared to those with no or minimal anticholinergic burden. Pooled analysis of adjusted mortality hazard ratios (HR) measured anticholinergic burden with the ACB scale, and suggested a significantly increased risk of death for those with a high ACB score relative to those with no or minimal ACB scores (HR 1.153, 95% confidence interval (CI) 1.030 to 1.292; 4 studies, 48,663 participants). An exploratory pooled analysis of adjusted mortality HRs across anticholinergic burden scales also suggested a significantly increased risk of death for those with a high anticholinergic burden (HR 1.102, 95% CI 1.044 to 1.163; 6 studies, 68,381 participants). Overall GRADE evaluation of results found low‐ or very low‐certainty evidence for all outcomes. Authors' conclusions: There is low‐certainty evidence that older adults with dementia or cognitive impairment who have a significant anticholinergic burden may be at increased risk of death. No firm conclusions can be drawn for risk of accelerated cognitive decline, neuropsychiatric disturbances, decline in physical function, or institutionalisation

Clinical implementation of preemptive pharmacogenomics in psychiatryResearch in context

Summary: Background: Pharmacogenomics (PGx) holds promise to revolutionize modern healthcare. Although there are several prospective clinical studies in oncology and cardiology, demonstrating a beneficial effect of PGx-guided treatment in reducing adverse drug reactions, there are very few such studies in psychiatry, none of which spans across all main psychiatric indications, namely schizophrenia, major depressive disorder and bipolar disorder. In this study we aim to investigate the clinical effectiveness of PGx-guided treatment (occurrence of adverse drug reactions, hospitalisations and re-admissions, polypharmacy) and perform a cost analysis of the intervention. Methods: We report our findings from a multicenter, large-scale, prospective study of pre-emptive genome-guided treatment named as PREemptive Pharmacogenomic testing for preventing Adverse drug REactions (PREPARE) in a large cohort of psychiatric patients (n = 1076) suffering from schizophrenia, major depressive disorder and bipolar disorder. Findings: We show that patients with an actionable phenotype belonging to the PGx-guided arm (n = 25) present with 34.1% less adverse drug reactions compared to patients belonging to the control arm (n = 36), 41.2% less hospitalisations (n = 110 in the PGx-guided arm versus n = 187 in the control arm) and 40.5% less re-admissions (n = 19 in the PGx-guided arm versus n = 32 in the control arm), less duration of initial hospitalisations (n = 3305 total days of hospitalisation in the PGx-guided arm from 110 patients, versus n = 6517 in the control arm from 187 patients) and duration of hospitalisation upon readmission (n = 579 total days of hospitalisation upon readmission in the PGx-guided arm, derived from 19 patients, versus n = 928 in the control arm, from 32 patients respectively). It was also shown that in the vast majority of the cases, there was less drug dose administrated per drug in the PGx-guided arm compared to the control arm and less polypharmacy (n = 124 patients prescribed with at least 4 psychiatric drugs in the PGx-guided arm versus n = 143 in the control arm) and smaller average number of co-administered psychiatric drugs (2.19 in the PGx-guided arm versus 2.48 in the control arm. Furthermore, less deaths were reported in the PGx-guided arm (n = 1) compared with the control arm (n = 9). Most importantly, we observed a 48.5% reduction of treatment costs in the PGx-guided arm with a reciprocal slight increase of the quality of life of patients suffering from major depressive disorder (0.935 versus 0.925 QALYs in the PGx-guided and control arm, respectively). Interpretation: While only a small proportion (∼25%) of the entire study sample had an actionable genotype, PGx-guided treatment can have a beneficial effect in psychiatric patients with a reciprocal reduction of treatment costs. Although some of these findings did not remain significant when all patients were considered, our data indicate that genome-guided psychiatric treatment may be successfully integrated in mainstream healthcare. Funding: European Union Horizon 2020

A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study

© 2023Background: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene–drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. Methods: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug–gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug–gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug–gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. Findings: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54–0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61–0·79]; p <0·0001). Interpretation: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. Funding: European Union Horizon 2020