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Surgery
Original research
Medication adherence of patients with peripheral arterial disease to antithrombotic therapy: a systematic review
  1. Emilien CJ Wegerif1,
  2. Barend M Mol1,
  3. Çağdaş Ünlü2,
  4. Gert J de Borst1,3
  1. 1 Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands
  2. 2 Vascular Surgery, Noordwest Ziekenhuisgroep, Alkmaar, Noord-Holland, The Netherlands
  3. 3 Vascular Surgery, Reinier de Graaf Gasthuis, Delft, The Netherlands
  1. Correspondence to Emilien CJ Wegerif; e.c.j.wegerif{at}umcutrecht.nl

Abstract

Objectives Antithrombotic therapy (ATT) prevents atherothrombotic events (AE) in patients with peripheral arterial disease (PAD). However, the benefit may be compromised by poor medication adherence (MA). Therefore, our primary objective was the proportion of patients with PAD with poor MA in literature following patient-reported, pharmacy-reported or laboratory-reported outcome measurements. Poor MA is a combined outcome of primary non-adherence (inability to initiate a prescription), secondary non-adherence (incorrect daily intake) and non-persistence (discontinuation of daily intake).

Design Systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

Data sources PubMed, EMBASE and Cochrane Library were searched from 2000 to June 2023.

Eligibility criteria Publications with a (sub)cohort of patients with PAD that reported on patients’ MA to ATT were included.

Data extraction and synthesis All articles were reviewed on eligibility and methodological quality by two independent researchers. The data were retrieved and collected in Review Manager Web and the percentages were calculated per subgroup. The risk of bias was assessed by using the Cochrane risk-of-bias tool for randomised controlled trials (RCT) and the methodological index for non-randomised studies score for non-RCTs.

Results We identified 274 potential records of which 10 studies (32 628 patients) were included. Six studies were RCTs and two prospective and two retrospective studies. Most studies scored a moderate risk of bias and had heterogeneous study designs. Poor MA rates ranged between 2% and 45%. Higher rates of poor MA were found in studies with longer follow-ups, pharmacy-reported outcome measurements and registry-based cohorts.

Conclusion Heterogeneous study designs create a wide dispersion in the proportions. However, poor MA to ATT was found in approximately one-third of the patients with PAD and seemed to increase with longer therapy duration, which highlights the magnitude of this societal challenge. Enhancing patients’ MA to ATT might be a key element in reducing the risk of AE, and therefore, more attention to MA in clinical and research settings is warranted.

PROSPERO registration number CRD42023431803.

  • Medication Adherence
  • Medication Persistence
  • Medication Review
  • Systematic Review
  • Vascular surgery
  • VASCULAR MEDICINE

Data availability statement

Data are available upon reasonable request. Access to the data is available via the correspondence of this article.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2024-085056

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    STRENGTHS AND LIMITATIONS OF THIS STUDY

    • This review is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and contains a comprehensive search compiled by a medical database specialist.

    • Studies regarding medication adherence of patients with peripheral arterial disease to antithrombotic therapy are scarce, leading to limited data.

    • The included trials had rather heterogeneous study designs, making a meta-analysis infeasible and creating a wide dispersion in medication adherence proportions.

    • This review provides insight into the extent of the patient’s poor medication adherence, which is an addition to the current literature focusing primarily on physician adherence.

    Introduction

    Peripheral arterial disease (PAD) is associated with a high risk of atherothrombotic events.1 2 The annual cardiovascular mortality risk of patients with intermittent claudication is approximately 5% compared with 11.5% for patients with critical limb-threatening ischaemia.3 In contrast to other atherosclerotic diseases such as coronary artery disease and cerebrovascular diseases, the overall long-term risk of major adverse cardiovascular events (MACE) in patients with PAD is twofold worse.4 5 In the last decades, revascularisation techniques have been improved, which resulted in a 40% reduction in major lower limb amputations; however, the high cardiovascular mortality risk has barely declined.1 2 6 7

    A cornerstone in PAD management is MACE prevention through pharmacological therapies through lifelong antihypertensives, statins and antithrombotic therapy (ATT).1 2 8 Medication adherence (MA), which is the ability to take medication following prescriptions, is believed to be an essential factor for pharmacological therapies to be effective.9 10 However, approximately 50% of patients with long-term medication due to chronic diseases in developed countries have poor MA.11 More specifically, in patients with cardiovascular protective medicines, poor MA was found in 25–80%.12–17 Nevertheless, the majority of these studies are outdated, focus on physician prescription adherence, primarily concentrate on patients without PAD diagnosis or non-ATTs. MA is partly influenced by overarching factors such as healthcare systems, but many factors are disease-related and patient-related such as clinical symptoms, socioeconomic background and medication side effects.15 18 19 This underscores the importance of reporting on MA rates in specific patient populations and medication groups.

    MA comprises two main elements: ‘adherence’ (or ‘compliance’) and ‘persistence’.9 15 No universally accepted consensus exists; however, adherence is mainly used to describe correct daily intake and persistence represents the continuation of daily intake.9 15 Adherence can be subdivided into primary (or initiation) and secondary adherence to differentiate between the ability to initiate a new prescription and the daily intake after initiating the first prescription. Patients are mostly considered adherent when approximately 80% of the intake is as prescribed.20 21 MA is measured through patient-reported (questionnaires), pharmacy-reported (counting pills, refill records) or biochemical/laboratory-reported outcome measurements (online supplemental table S1).22

    Supplemental material

    The optimal ATT in patients with PAD is still under debate.1 8 23 24 MA is generally not discussed in trials, although poor MA might lead to substantial bias and thus erroneous outcomes. As far as we know, there are no systematic analyses regarding MA of patients with PAD to ATT. Therefore, we initiated this study to assess medication adherence specifically for ATT in patients with PAD.

    Methods

    The protocol of this systematic review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PROSPERO: CRD42023431803).25 26

    Search strategy and study selection

    The systematic literature search was performed from inception to 7 June 2023. The bibliographic databases PubMed, Embase.com and Wiley/Cochrane Library were used. The index terms ‘Peripheral Arterial Disease’, ‘Antithrombotic Drugs’ and ‘Treatment Adherence and Compliance’ along with their synonyms and/or closely related words were included. The search was compiled by a medical database specialist (see online supplemental figures S1–S3).

    The search results were first deduplicated to which all obtained articles were screened on title and abstract by two independent researchers (ECJW and BMM). Subsequently, the remaining articles were fully reviewed for eligibility, and the references were screened for relevant publications (online supplemental figure S4). In case of disagreement, the study was reviewed by a third reviewer (CU).

    Eligible publications contained a (sub)population of adult patients with PAD and reported on patients’ (non)adherence and/or (non)persistence to ATT. Publications before the year 2000, review articles, expert opinions, case reports, use of polypills, only nurse-led intensified follow-up and non-English articles were excluded (online supplemental figure S4).

    Outcome definitions and measurements

    The primary objective was the proportion of patients with PAD with poor MA following patient-reported, pharmacy-reported or biochemical/laboratory-reported outcome measurements (online supplemental table S1). Poor MA includes primary non-adherence (the inability to initiate a new prescription), secondary non-adherence (incorrect daily dosage/timing/frequency after initiating a new prescription) and non-persistence (discontinuation of the medication intake).9 15 22

    Secondary objectives were the proportion of patients with PAD with (1) poor MA following pharmacy-reported outcome measurements, (2) primary non-adherence following pharmacy-reported and (3) all outcome measurements, (4) secondary (short- and long-term) non-adherence following pharmacy-reported and (5) all outcome measurements and (6) non-persistence following pharmacy-reported and (7) all outcome measurements. Short-term was defined as a maximum follow-up of 6 months, and long-term follow-up was defined as more than 6 months.

    Data extraction and data analysis

    The extracted data included first author, year of publication, study design, country, number of patients with PAD, disease stage, mean age, male–female ratio, type of ATT, type of MA subgroup(s), number of patients with PAD that had poor MA per subgroup, number of patients with PAD with overlap between two or more MA subgroups, threshold for poor MA, follow-up length and MA outcome measurement.

    The data were retrieved and collected in Review Manager Web (RevMan Web), V.4.14.0, The Cochrane Collaboration, London, UK. Based on the number of patients with PAD with poor MA per subgroup and the total number of patients with PAD, the proportions of non-adherence/non-persistence were calculated per subgroup and processed in the table. For the primary objective, that is, general poor MA, a separate calculation was made to adjust for patients with two or more kinds of poor MA to avoid overestimation of the general poor MA. Clinical homogeneity was assessed based on the study designs and definitions of non-adherence and/or non-persistence.

    Quality assessment

    The Cochrane Risk-of-Bias (ROB) tool was applied to assess the quality of the included randomised controlled trials (RCTs) that reported MA as the primary outcome. The Cochrane ROB tool identifies different domains of bias and classifies risk into high, low or unclear risk.27 The overall quality was deemed high if all domains had a low ROB or if 1 domain was unclear. Unclear ROB was considered if ≥2 domains were unclear, and high ROB was assigned if ≥1 domain had a high ROB.

    For the non-RCTs and RCTs that report MA as a subanalysis, the methodological index for non-randomised studies (MINORS) score was used.28 This method provides a 12-item list for comparative studies and an 8-item list for non-comparative studies. This score contains three classes: 0 (not reported), 1 (reported inadequate) and 2 (reported adequate). The overall quality for non-comparative trials was considered poor if the score was ≤8, moderate between 9–14 and good if ≥15. For the comparative trials, the score ranges were ≤15, 16–22 and ≥23.

    Patient and public involvement

    None.

    Results

    Screening process

    The search identified 274 potentially relevant records after deduplicating. No articles were added by cross-linking. After reviewing the title and abstract, 227 articles were excluded and 4 articles could not be retrieved. The remaining 45 records were fully screened of which 10 records could be included: 6 RCTs, 2 prospective and 2 retrospective studies (online supplemental figure S1). In case of conflicting screening decisions, consensus was reached between ECJW and BMM.

    Risk-of-bias assessment

    Three articles were RCTs with MA as the main analysis of the trial, and therefore, the Cochrane ROB tool was used (online supplemental table S2). The MINORS score was used for the other seven articles (online supplemental table S3). Overall, most studies had a moderate ROB. Concerns regarding the ROB arise mostly due to patient-reported outcomes and non-adjudicated endpoints that could be easily influenced by knowledge of the intervention. Moreover, most articles did not calculate a sample size based on the MA outcome.

    Study sample/study characteristics

    The characteristics of the included studies are shown in table 1. In total, 32 628 patients with PAD were analysed. Most studies were executed in Europe; however, the two largest trials (EUCLID and VOYAGER PAD) that accounted for 63% of the included patients were executed in various countries and continents.29 30 MA was mostly reported as a subanalysis. The included trials had rather heterogeneous study designs, making a meta-analysis infeasible.

    View this table:
    Table 1

    Articles eligible for this systematic review

    Medication adherence

    Poor MA following all outcome measurements ranged between 2% and 45% and following pharmacy-reported measurements between 9% and 45% (table 2). One study, however, reported on all three subcategories of poor MA (ie, primary, secondary adherence and persistence) and reported a total risk of 33%.31 Overall, higher proportions of poor MA were found in studies with longer follow-ups, pharmacy-reported outcomes and registry-based methods.31–33

    View this table:
    Table 2

    Medication adherence

    One study reported on primary non-adherence based on a pharmacy-reported outcome measurement that occurred in 31% of the study population (table 2). Short-term secondary non-adherence was reported in three articles and ranged between 9% and 26% (table 2). Two of the three articles applied pharmacy-reported outcome measurement and found rates between 9% and 21%. Long-term secondary non-adherence, described in five articles, showed rates ranging between 5% and 26% comparable to short-term secondary non-adherence (table 2). Following the pharmacy-reported outcome measurement, long-term secondary non-adherence occurred in 14–20% of the patients. Lastly, non-persistence was found between 2% and 33% (table 2). Non-persistence within the pharmacy-reported group ranged between 27% and 33%. Higher rates of non-persistence were found in studies with longer follow-ups and registry-based methods.

    Discussion

    This systematic review provides an overview of the literature about MA to ATT in patients with PAD. The results demonstrate a poor MA rate of approximately one-third. Despite the variability in poor MA rates, it shows the magnitude of poor MA. Higher rates of poor MA were found in studies with longer follow-ups, pharmacy-reported outcomes and registry-based methods. The secondary objectives show that all subcategories seem to have a nearly equal share in the overall risk of non-adherence.

    Trial designs influence participant burdens, which might partly explain the dispersion in MA among trials.34 35 In this review, three articles required minimum effort from participants because of the registry-based or retrospective design compared with the other articles including extensive follow-up, additional injections and/or blood samples. Designs that required minimum effort showed the highest rate of poor MA, non-adherence and/or non-persistence.31 33 36 In the field of PAD, it is plausible that the likelihood of creating a more representative sample rises as the required effort for patients decreases. Literature shows that patients with PAD are frequently precarious, which is related to lower socioeconomic status and, therefore, less likely to participate in trials.12 37–40 Reducing the complexity of trials leads to better understanding, fewer transfers, time commitment and risk of additional (transfer) costs, resulting in a lower threshold for participation in this population.35

    Regarding the length of follow-up, the literature shows a tendency for poor MA to increase as the duration of medication use increases.41–43 This review shows similar results (table 2). One study provided a subanalysis (data not included in our tables) revealing that the highest proportion of non-adherence predominantly occurred between 13 and 24 months with 44% and 35.5%, respectively, compared with 17% within the first 12 months.33 This pattern corresponds with the dispersion in our long-term non-adherence results (table 2).

    Additionally, the heterogeneity of the reporting methods, such as the definition of MA and outcome measurements, might contribute to the variety in proportions between studies. MA includes three subcategories: primary non-adherence, secondary non-adherence and non-persistence. Most articles, except one, researched only non-persistence and/or secondary non-adherence. This might underestimate the proportion of poor MA by not identifying all categories of MA. The study that distinguished all three subcategories reported the highest proportion of poor MA.31

    Healthcare systems have a major influence on MA.15 18 19 37 One study showed that participants from North America were more likely to discontinue their medication compared with participants from Europe.29 Another study executed in North America confirmed that the inability to afford medication was a major reason for poor MA.36 Most European countries have similar healthcare systems that reimburse necessary health costs.44

    Regarding patient-related factors, studies that include postrevascularised patients with PAD might show slightly higher MA rates.30 32 45 One study showed lower long-term secondary non-adherence compared with short-term non-adherence.32 These patients underwent revascularisation at 6 months follow-up. The severity of the symptoms might affect patients’ perception of treatments. However, the literature is ambiguous.36 Equivocal evidence regarding the impact of patient-related factors on MA is common. Among the included studies, subanalyses of patient-related factors show heterogeneous results.29 30 33 36 46

    To estimate the individual risk of poor MA, it is of interest whether non-adherence leads to non-persistence. It seems that adherent and non-adherent patients are both highly at risk for non-persistence and thus poor MA.33 The reason given is the lack of awareness regarding the life-long indication for ATT in patients with PAD. We advise physicians to discuss MA with patients with PAD. Additional research on all subcategories of MA based on registries that use pharmacy refill records and have extensive follow-up are warranted to confirm our findings.

    The main strengths of this study are the selected inclusion of trials that include medication adherence of patients with PAD regarding antithrombotic therapies and the distinction between different types of adherence which is clinically relevant when prescribing and discussing antithrombotic treatment. However, this review has a few limitations. Six out of the 10 included articles are RCTs. RCTs may not reflect real-world adherence as these patients are often more closely monitored and, therefore, more motivated. Most articles were at moderate risk for bias, and a few studies did not mention their thresholds for non-adherence. Moreover, the heterogeneous study designs made a meta-analysis infeasible. Most of the included studies used patient-reported outcome measurements, that is, questionnaires and interviews, which are at risk for multiple biases such as recall bias leading to potentially misleading low rates of poor MA.13 32 47

    Conclusion

    Studies regarding MA in patients with PAD to ATT are scarce and contain heterogeneous designs creating a wide dispersion in MA proportions. However, poor MA to ATT was found in approximately one-third of the patients with PAD and seemed to increase with longer duration of ATT use, which highlights the magnitude of this societal challenge.

    Data availability statement

    Data are available upon reasonable request. Access to the data is available via the correspondence of this article.

    Ethics statements

    Patient consent for publication

    Ethics approval

    Not applicable.

    References

    1. ↵
      2. Aboyans V ,
      3. Ricco J-B ,
      4. Bartelink M-L , et al
      . Editor’s Choice - 2017 ESC Guidelines on the Diagnosis and Treatment of Peripheral Arterial Diseases, in collaboration with the European Society for Vascular Surgery (ESVS). Eur J Vasc Endovasc Surg 2018;55:305–68. doi:10.1016/j.ejvs.2017.07.018
      OpenUrlCrossRefPubMed
    2. ↵
      2. Twine CP ,
      3. Kakkos SK ,
      4. Aboyans V , et al
      . Editor’s Choice - European Society for Vascular Surgery (ESVS) 2023 Clinical Practice Guidelines on Antithrombotic Therapy for Vascular Diseases. Eur J Vasc Endovasc Surg 2023;65:627–89. doi:10.1016/j.ejvs.2023.03.042
      OpenUrl
    3. ↵
      2. van Haelst STW ,
      3. Koopman C ,
      4. den Ruijter HM , et al
      . Cardiovascular and all-cause mortality in patients with intermittent claudication and critical limb ischaemia. Br J Surg 2018;105:252–61. doi:10.1002/bjs.10657
      OpenUrl
    4. ↵
      2. Welten GMJM ,
      3. Schouten O ,
      4. Hoeks SE , et al
      . Long-term prognosis of patients with peripheral arterial disease: a comparison in patients with coronary artery disease. J Am Coll Cardiol 2008;51:1588–96. doi:10.1016/j.jacc.2007.11.077
      OpenUrlFREE Full Text
    5. ↵
      2. Steg PG ,
      3. Bhatt DL ,
      4. Wilson PWF , et al
      . One-year cardiovascular event rates in outpatients with atherothrombosis. JAMA 2007;297:1197–206. doi:10.1001/jama.297.11.1197
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      2. Barnes JA ,
      3. Eid MA ,
      4. Creager MA , et al
      . Epidemiology and Risk of Amputation in Patients With Diabetes Mellitus and Peripheral Artery Disease. Arterioscler Thromb Vasc Biol 2020;40:1808–17. doi:10.1161/ATVBAHA.120.314595
      OpenUrl
    7. ↵
      2. Voci D ,
      3. Fedeli U ,
      4. Valerio L , et al
      . Mortality rate related to peripheral arterial disease: A retrospective analysis of epidemiological data (years 2008-2019). Nutr Metab Cardiovasc Dis 2023;33:516–22. doi:10.1016/j.numecd.2022.11.020
      OpenUrl
    8. ↵
      2. Conte MS ,
      3. Pomposelli FB ,
      4. Clair DG , et al
      . Society for Vascular Surgery practice guidelines for atherosclerotic occlusive disease of the lower extremities: Management of asymptomatic disease and claudication. J Vasc Surg 2015;61:2S–41S. doi:10.1016/j.jvs.2014.12.009
      OpenUrlCrossRefPubMed
    9. ↵
      2. Cramer JA ,
      3. Roy A ,
      4. Burrell A , et al
      . Medication compliance and persistence: terminology and definitions. Value Health 2008;11:44–7. doi:10.1111/j.1524-4733.2007.00213.x
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      2. Simpson SH ,
      3. Eurich DT ,
      4. Majumdar SR , et al
      . A meta-analysis of the association between adherence to drug therapy and mortality. BMJ 2006;333:15. doi:10.1136/bmj.38875.675486.55
      OpenUrlAbstract/FREE Full Text
    11. ↵
      2. Sabaté E
      . Adherence to long-term therapies: evidence for action. World Health Organization, 2003.
    12. ↵
      2. Baroletti S ,
      3. Dell’Orfano H
      . Medication adherence in cardiovascular disease. Circulation 2010;121:1455–8. doi:10.1161/CIRCULATIONAHA.109.904003
      OpenUrlFREE Full Text
    13. ↵
      2. Naderi SH ,
      3. Bestwick JP ,
      4. Wald DS
      . Adherence to drugs that prevent cardiovascular disease: meta-analysis on 376,162 patients. Am J Med 2012;125:882–7. doi:10.1016/j.amjmed.2011.12.013
      OpenUrlCrossRefPubMed
    14. ↵
      2. Memon RA ,
      3. Raveena Bai B ,
      4. Simran F , et al
      . Effect of the Polypill on Adherence and Prevention of Cardiovascular Diseases in Patients With or at High Risk of Cardiovascular Diseases: A Meta-Analysis of Randomized Controlled Trials. Cureus 2023;15:e34134. doi:10.7759/cureus.34134
    15. ↵
      2. Ho PM ,
      3. Bryson CL ,
      4. Rumsfeld JS
      . Medication adherence: its importance in cardiovascular outcomes. Circulation 2009;119:3028–35. doi:10.1161/CIRCULATIONAHA.108.768986
      OpenUrlAbstract/FREE Full Text
    16. ↵
      2. Flu HC ,
      3. Tamsma JT ,
      4. Lindeman JHN , et al
      . A systematic review of implementation of established recommended secondary prevention measures in patients with PAOD. Eur J Vasc Endovasc Surg 2010;39:70–86. doi:10.1016/j.ejvs.2009.09.027
      OpenUrlCrossRefPubMed
    17. ↵
      2. Chan SL ,
      3. Rajesh R ,
      4. Tang TY
      . Evidence-based medical treatment of peripheral arterial disease: A rapid review. Ann Acad Med Singap 2021;50:411–24. doi:10.47102/annals-acadmedsg.2020649
      OpenUrl
    18. ↵
      2. Kardas P ,
      3. Lewek P ,
      4. Matyjaszczyk M
      . Determinants of patient adherence: a review of systematic reviews. Front Pharmacol 2013;4:91. doi:10.3389/fphar.2013.00091
      OpenUrlCrossRefPubMed
    19. ↵
      2. Osterberg L ,
      3. Blaschke T
      . Adherence to medication. N Engl J Med 2005;353:487–97. doi:10.1056/NEJMra050100
      OpenUrlCrossRefPubMedWeb of Science
    20. ↵
      2. Svarstad BL ,
      3. Chewning BA ,
      4. Sleath BL , et al
      . The Brief Medication Questionnaire: a tool for screening patient adherence and barriers to adherence. Patient Educ Couns 1999;37:113–24. doi:10.1016/s0738-3991(98)00107-4
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      2. Karve S ,
      3. Cleves MA ,
      4. Helm M , et al
      . Good and poor adherence: optimal cut-point for adherence measures using administrative claims data. Curr Med Res Opin 2009;25:2303–10. doi:10.1185/03007990903126833
      OpenUrlCrossRefPubMed
    22. ↵
      2. Lam WY ,
      3. Fresco P
      . Medication Adherence Measures: An Overview. Biomed Res Int 2015;2015:217047. doi:10.1155/2015/217047
      OpenUrl
    23. ↵
      2. Gerhard-Herman MD ,
      3. Gornik HL ,
      4. Barrett C , et al
      . 2016 AHA/ACC Guideline on the Management of Patients with Lower Extremity Peripheral Artery Disease: Executive Summary. Vasc Med 2017;22:NP1–43. doi:10.1177/1358863X17701592
      OpenUrlPubMed
    24. ↵
      2. Willems LH ,
      3. Maas DPMSM ,
      4. Kramers K , et al
      . Antithrombotic Therapy for Symptomatic Peripheral Arterial Disease: A Systematic Review and Network Meta-Analysis. Drugs (Abingdon Engl) 2022;82:1287–302. doi:10.1007/s40265-022-01756-6
      OpenUrl
    25. ↵
      2. Page MJ ,
      3. Moher D ,
      4. Bossuyt PM , et al
      . PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ 2021;372:n160. doi:10.1136/bmj.n160
      OpenUrlFREE Full Text
    26. ↵
      2. Rethlefsen ML ,
      3. Kirtley S ,
      4. Waffenschmidt S , et al
      . PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Syst Rev 2021;10:39. doi:10.1186/s13643-020-01542-z
      OpenUrlCrossRefPubMed
    27. ↵
      2. Higgins JPT ,
      3. Altman DG ,
      4. Gøtzsche PC , et al
      . The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 2011;343:d5928. doi:10.1136/bmj.d5928
      OpenUrlFREE Full Text
    28. ↵
      2. Slim K ,
      3. Nini E ,
      4. Forestier D , et al
      . Methodological index for non-randomized studies (minors): development and validation of a new instrument. ANZ J Surg 2003;73:712–6. doi:10.1046/j.1445-2197.2003.02748.x
      OpenUrlCrossRefPubMedWeb of Science
    29. ↵
      2. Weissler EH ,
      3. Mulder H ,
      4. Rockhold FW , et al
      . Understanding Study Drug Discontinuation Through EUCLID. Front Cardiovasc Med 2022;9:947645. doi:10.3389/fcvm.2022.947645
      OpenUrl
    30. ↵
      2. Hess CN ,
      3. Baumgartner I ,
      4. Anand SS , et al
      . Sex-Based Differences in Outcomes Following Peripheral Artery Revascularization: Insights From VOYAGER PAD. J Am Heart Assoc 2022;11:e024655. doi:10.1161/JAHA.121.024655
    31. ↵
      2. Qvist I ,
      3. Søgaard R ,
      4. Lindholt JS , et al
      . Adherence to Prescribed Drugs Among 65-74 Year Old Men Diagnosed with Abdominal Aortic Aneurysm or Peripheral Arterial Disease in a Screening Trial: A VIVA Substudy. Eur J Vasc Endovasc Surg 2019;57:442–50. doi:10.1016/j.ejvs.2018.09.023
      OpenUrl
    32. ↵
      2. Haile ST ,
      3. Joelsson-Alm E ,
      4. Johansson UB , et al
      . Effects of a person-centred, nurse-led follow-up programme on adherence to prescribed medication among patients surgically treated for intermittent claudication: randomized clinical trial. Br J Surg 2022;109:846–56. doi:10.1093/bjs/znac241
      OpenUrl
    33. ↵
      2. Wawruch M ,
      3. Murin J ,
      4. Tesar T , et al
      . Adherence to Antiplatelet Medications among Persistent and Non-Persistent Older Patients with Peripheral Arterial Disease. Biomedicines 2021;9:12. doi:10.3390/biomedicines9121800
      OpenUrl
    34. ↵
      2. Cameron D ,
      3. Willoughby C ,
      4. Messer D , et al
      . Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient. Clin Ther 2020;42:e150–9. doi:10.1016/j.clinthera.2020.06.015
      OpenUrl
    35. ↵
      2. Getz K ,
      3. Sethuraman V ,
      4. Rine J , et al
      . Assessing Patient Participation Burden Based on Protocol Design Characteristics. Ther Innov Regul Sci 2020;54:598–604. doi:10.1007/s43441-019-00092-4
      OpenUrl
    36. ↵
      2. Halle TR ,
      3. Benarroch-Gampel J ,
      4. Teodorescu VJ , et al
      . Surgical Intervention for Peripheral Artery Disease Does Not Improve Patient Compliance with Recommended Medical Therapy. Ann Vasc Surg 2018;46:104–11. doi:10.1016/j.avsg.2017.06.152
      OpenUrl
    37. ↵
      2. De Geest S ,
      3. Sabaté E
      . Adherence to long-term therapies: evidence for action. Eur J Cardiovasc Nurs 2003;2:323. doi:10.1016/S1474-5151(03)00091-4
      OpenUrlCrossRefPubMed
    38. ↵
      2. Joly M ,
      3. Gillois P ,
      4. Satger B , et al
      . Comparative evaluation of socioeconomic insecurity in peripheral and coronary artery disease patients. J Med Vasc 2022;47:220–7. doi:10.1016/j.jdmv.2022.10.001
      OpenUrl
    39. ↵
      2. Ohm J ,
      3. Jernberg T ,
      4. Johansson D , et al
      . Association of clinical trial participation after myocardial infarction with socioeconomic status, clinical characteristics, and outcomes. Eur Heart J Open 2021;1:oeab020. doi:10.1093/ehjopen/oeab020
    40. ↵
      2. Chang P ,
      3. Nead KT ,
      4. Olin JW , et al
      . Clinical and socioeconomic factors associated with unrecognized peripheral artery disease. Vasc Med 2014;19:289–96. doi:10.1177/1358863X14535475
      OpenUrlCrossRefPubMed
    41. ↵
      2. Krousel-Wood M ,
      3. Joyce C ,
      4. Holt E , et al
      . Predictors of decline in medication adherence: results from the cohort study of medication adherence among older adults. Hypertension 2011;58:804–10. doi:10.1161/HYPERTENSIONAHA.111.176859
      OpenUrlCrossRefPubMed
    42. ↵
      2. Newby LK ,
      3. LaPointe NMA ,
      4. Chen AY , et al
      . Long-term adherence to evidence-based secondary prevention therapies in coronary artery disease. Circulation 2006;113:203–12. doi:10.1161/CIRCULATIONAHA.105.505636
      OpenUrlAbstract/FREE Full Text
    43. ↵
      2. Jackevicius CA ,
      3. Mamdani M ,
      4. Tu JV
      . Adherence with statin therapy in elderly patients with and without acute coronary syndromes. JAMA 2002;288:462–7. doi:10.1001/jama.288.4.462
      OpenUrlCrossRefPubMedWeb of Science
    44. ↵
      2. Davis K ,
      3. Stremikis K ,
      4. Squires D , et al
      . Mirror, mirror on the wall. How the performance of the us health care system compares internationally. New York: CommonWealth Fund, 2014.
    45. ↵
      2. Cassar K ,
      3. Bachoo P ,
      4. Ford I , et al
      . Variability in responsiveness to clopidogrel in patients with intermittent claudication. Eur J Vasc Endovasc Surg 2006;32:71–5. doi:10.1016/j.ejvs.2006.01.013
      OpenUrlCrossRefPubMed
    46. ↵
      2. Ferreira-González I ,
      3. Marsal JR ,
      4. Ribera A , et al
      . Background, incidence, and predictors of antiplatelet therapy discontinuation during the first year after drug-eluting stent implantation. Circulation 2010;122:1017–25. doi:10.1161/CIRCULATIONAHA.110.938290
      OpenUrlAbstract/FREE Full Text
    47. ↵
      2. Zini MLL ,
      3. Banfi G
      . A Narrative Literature Review of Bias in Collecting Patient Reported Outcomes Measures (PROMs). Int J Environ Res Public Health 2021;18:23. doi:10.3390/ijerph182312445
      OpenUrl
      2. Jivegård L ,
      3. Drott C ,
      4. Gelin J , et al
      . Effects of three months of low molecular weight heparin (dalteparin) treatment after bypass surgery for lower limb ischemia--a randomised placebo-controlled double blind multicentre trial. Eur J Vasc Endovasc Surg 2005;29:190–8. doi:10.1016/j.ejvs.2004.11.011
      OpenUrlCrossRefPubMedWeb of Science
      2. Kremers BMM ,
      3. Daemen JHC ,
      4. Ten Cate H , et al
      . Inadequate response to antiplatelet therapy in patients with peripheral artery disease: a prospective cohort study. Thromb J 2023;21:5. doi:10.1186/s12959-022-00445-4
      OpenUrl

    Footnotes

    • Contributors ECJW: Concept and design, screening, data collection, analyses and interpretation of data, writing of manuscript and final approval. BMM: Screening, data collection and analyses, and final approval. CU: Concept and design, revision of manuscript and final approval. G-JdB: Concept and design, revision of manuscript, final approval and is the guarantor.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.