Factors Influencing Adherence to Imatinib in Indian Chronic Myeloid Leukemia Patients: A Cross-Sectional Study
Jyotsna Kapoor1, Narendra Agrawal2, Rayaz Ahmed2, Sanjeev Kumar Sharma3, Anshul Gupta2 and Dinesh Bhurani2
1 Masters in
Clinical Research, Department of Hematology,
Rajiv Gandhi Cancer Institute and
Research Centre, Sector - 5, Rohini,
Delhi, India. PIN 110085
2 DM, Consultant Hematology, Department of Hematology, Rajiv Gandhi Cancer Institute and Research Centre, Sector - 5, Rohini, Delhi, India. PIN 110085
3 DM, Consultant Hematology, Hemato-Oncology and BMT Unit, BLK Superspeciality Hospital, Rajendra Place, New Delhi, India, PIN 110008
Received: November 9, 2014
Accepted: February 2, 2015
Mediterr J Hematol Infect Dis 2015, 7(1): e2015013, DOI 10.4084/MJHID.2015.013
This article is available on PDF format at:
| This is an Open Access article distributed
under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Adherence to imatinib (IM) is of utmost importance in patients with chronic myeloid leukemia (CML) to maximise treatment effectiveness. The main objective is to measure adherence to IM by evaluating individual patient characteristics, personal behaviour and, treatment related psychological factors influencing adherence behaviour. Hundred patients receiving IM were analysed for adherence behaviour using 9 item Morisky Medication Adherence Scale (9-MMAS). Various factors were assessed for their impact on adherence behaviour. These factors were age, gender, duration of treatment, frequency and dosing of treatment, use of tobacco and alcohol, educational qualification, employment status, monthly income, side effects, financial assistance in treatment, social support, knowledge about medicine and disease, concomitant drug burden, polypharmacy, physician patient interaction, patient educational sessions and prevalence of depression. Seventy five percent of patients were found to be adherent. On univariate analysis, prevalence of depression (p<0.000001), moderate severe depression (p<0.000001), concomitant drug burden (p=0.036) and monthly income (p=0.015) were found to be significantly influencing adherence. The final multivariate model retained prevalence of depression with OR= 10.367 (95% CI, 3.112- 34.538) as independent predictor of adherence to therapy. This study suggests that identification and treatment of depression among CML patients may further enhance adherence to IM therapy.
More than a decade ago, revolution came in the treatment of CML with
the introduction of the Imatinib Mesylate (IM), a BCR- ABL tyrosine
kinase inhibitor. After 5 years of follow – up, continuous treatment of
chronic – phase CML with imatinib, as initial therapy, was found to
induce durable responses in a high proportion of patients.[1,2] With IM
being so effective, the allogenic stem cell transplantation no longer
remains the first line treatment, despite being a curative treatment.
Though IM is the first line treatment, few drawbacks are associated
with its use as it is still not considered to be a curative therapy; it
requires indefinite treatment on daily basis and ensuring optimal
adherence to treatment for long term. Adherence to medication has been
recently defined by an international panel of experts as ‘the process
by which patients take their medications as prescribed’ and this
process has three main components: initiation, implementation, and
Various studies and several case reports have shown that non adherence to IM is common[4-10,13] and intertwined with non-achievement of molecular responses[4,5,7,10] and event free survival emphasising strict adherence to the prescribed dose of IM holds paramount importance to maximise treatment effectiveness in CML patients. For example, a Belgian study found that one third of the patients were non adherent and only 14% were adherent to all the prescribed dose. On average, patients with suboptimal response had significantly higher mean percentages of IM not taken (23.2%,standard deviation [SD] 23.8) than did those with optimal response (7.3%, SD 19.3, P.005), Marin et al found that 26% of the patients had adherence rate <90% (considered to be nonadherent) and adherence is a critical factor for achieving molecular responses in patients with CML who achieve complete cytogenetic responses on IM. Darkow et al found 31% of nonadherence rate among US CML population using electronic data of dispensation of IM and also found non- adherence led to increased healthcare costs. Adherence to IM have been also studied in the past in Indian population using records of Glivec International Patient Assistance Program (GIPAP) retrospectively in which one third of the patients were found to be non-adherent to IM and concluded that non- adherence to IM adversely affects event free survival (EFS) in chronic phase CML (CP-CML) patients.
There is scarce availability of literature citing the potential reasons for non-adherence to oral anticancer treatment and few existing data on reasons why CML patients might be non- adherent to IM. Treatment related aspects (side effects, knowledge of disease or treatment, financial cost of treatment etc.), individual patient characteristics (gender, age) and personal factors (social support) have been found to be influencing adherence in chronic illnesses.[11-13] We hypothesized that these factors might affect adherence to IM in CML patients too. Ganesan et al tried to explore reasons of non- adherence to IM in Indian CML patients and assessed age, sex, economic status and Sokal score. No study has completely investigated the treatment related, individual patient characteristics, personal and psychological factors influencing adherence in Indian patients with CML so far. Therefore, we conducted this personal interview based study to assess the adherence of CML patients using 9 MMAS and to evaluate personal, treatment related, and psychological factor associated with adherence at Rajiv Gandhi Cancer Institute and Research Centre, India.
Study Design and Setting.
This study was carried out at Rajiv Gandhi Cancer Institute and
Research Centre, Delhi, India. All CML patients over 18 years of age
and below 80 years, with ongoing IM therapy for minimum duration of
three months, and who visited the outpatient department during a period
of February 2013 and May 2013 were considered for inclusion in the
study. Patients who were dumb and/or deaf or undergone allogenic
hematopoietic stem cell transplant were excluded from the study. The
questionnaires were available in Hindi and English, the patients who
did not understand these languages were excluded. The patients included
in the study were taking IM either 400mg/day or 600mg/day or 800mg/day.
The patients who were taking 600mg/day or 800mg/day were advised to
take half the dose after heavy meal in the morning and the other half
dose after heavy meal in the evening to manage the gastric side
effects. Optimal sample size was calculated and found to be 84 in
accordance with the previous adherence study conducted on Indian
population by Ganesan et al (30% of non-adherence rate was found), we
approximated the sample size to be 100. The total number of patients
visiting the OPD within this period were 139 and 82.7% (115 patients)
of these fulfilled the inclusion criteria.
The questionnaire was translated by official translators in Hindi allowing the majority of patients to undergo personal interview in their native language. The patients were given oral and written information regarding the study when asked to participate. After giving oral and written consent for participation, the study coordinator personally interviewed the patients using questionnaires in their preferred language. This study was approved by the Institutional Review Board of our centre. This study was conducted in accordance with latest version of Declaration of Helsinki.
Questionnaires. The questionnaire used consisted of 9-MMAS (to measure adherence behaviour), additional questionnaire (to assess the factors influencing adherence except depression) and PHQ-9 (to assess prevalence of depression). The questionnaire asked about adherence behaviour, socio-demographic background, knowledge about disease and medicine, social support, physician patient relationship, role of patient educational sessions, side effects of medicine, financial assistance in treatment, concomitant drug burden, polypharmacy, details about therapy, and depression. Additional questionnaire was partly devised from questionnaire, previously used by Jonsonn et al9 and questions regarding role of patient educational sessions, polypharmacy, financial assistance in treatment and concomitant drug burden were added in view of our cohort. The internal consistency reliability of the combined questionnaire to assess the factors influencing adherence (additional questionnaire and PHQ-9), using Crohnbach α was found to be 0.72.
Adherence Behaviour. The 9-item Morisky Medication Adherence Scale (9-MMAS), a standardised test, was used to measure adherence, with scores ranging from 1-13, where 13 indicates perfects adherence. This test has been developed from the well validated Morisky Green Test and the eight item MMAS.[15,16] The internal consistency reliability of the English version of 9- item MMAS, measured by the Crohnbach α, had a value of 0.89. The 9- item MMAS is composed of 9 questions explores adherence behaviour based on forgetfulness, negligence, interruption of drug intake and restart of drug intake when symptoms worsen. Patients scoring 11 or above in the summary score were classified as adherent. This definition of adherence is based on how patients theoretically would have completed the MMAS if they had taken at least 95% of prescribed doses.
Factors Influencing Adherence. Socio-demographic background composed of 8 questions asking about gender, age, marital status, employment status, educational qualification, monthly income, and use of tobacco or alcohol in any form. For example, with regard to employment status, a question was asked ‘Do you work?’ with an option of ‘Yes/No’. Knowledge about Medicine and Disease composed of 5 questions along with subparts to find out whether the respondents have basic knowledge about their disease and treatment. For each correct answer ‘1’ was scored. Support given by family, friends and colleagues was assessed using 10 questions comprising of Yes/No option. A healthy and regular physician patient interaction was assessed using a set of 7 questions followed by a Yes/ No option except one question. Questions included were ‘Do you visit your physician at regular intervals?’, ‘Do you feel the physician is very helpful to you?’ ‘Do you trust your physician?’etc. Patients were interviewed whether they have attended the last patient educational session on CML and if yes, did they found it helpful to find out the role of patient educational sessions on adherence. Patients were questioned about being financially assisted in treatment, if so, and then what were the means of assistance. Concomitant drug burden was defined as the assumption of additional drugs related to diseases other than CML may affect the adherence to IM (Yes/No). Polypharmacy was defined as taking at least one alternative medicine apart from IM for CML (Yes/No) may affect the adherence to IM. Commonly used alternative medicines were from ayurvedic, homeopathic and unani system of medicine. Patients were also questioned about the side effects if they ever had with the use of imatinib and if they had, the side effects were recorded accordingly. The prevalence of depression among CML patients was evaluated with a Patient Health Questionnaire-9 (PHQ -9), a validated and standardized instrument with good specificity and sensitivity. The PHQ-9 focuses on the nine signs and symptoms of depression from DSM-IV. In addition, the sum score of PHQ-9 (0-27) is used for screening purposes and for measuring depression severity. As a severity measure the PHQ-9 score can range from 0-27, since each of the 9 items can be scored from 0 (Not at all) to 3 (Nearly every day).
Multiple logistic regression analysis was used to identify factors associated with adherence. For variable selection in the model, the backward stepwise likelihood ratio method was used to perform regression analysis with probability less than 0.3. Data were analyzed using SPSS version 21.0 (2012, IBM Corp, Armonk, NY, USA) and p value <0.05 was considered of statistical significance.
In this study, 100 out of 115 eligible patients completed the interview (response rate 86.9%) (Figure 1). 51% of the respondents were interviewed in Hindi language.
|Figure 1. Patient Recruitment Details|
Descriptive Statistics. Descriptive statistical data of 100 patients analyzed are present in Table 1. The majority of the respondents were male (63%) and the mean age was 41.08 years (range 18-70) and median duration of imatinib therapy was 30 months (range 3-101).
|Table 1. Socio Demographic, Clinical, Personal, and Treatment Related Factors|
Adherence Behaviour. All patients included
in the study (n=100) completed the 9-MMAS. The median Morisky Score of
100 patients included was 12 (Range; 7-13). 75 (50 male and 25 female)
out of 100 patients had Morisky score ≥ 11, therefore classified as
adherent. Twenty two percent of the respondents scored 13, i.e. perfect
adherence. Forty six percent of the respondents had special routine or
reminder system which helps them taking medication. Ninety three
percent patients took their medicine prior to the day of interview.
None of the patients had summary score <5. Four out of twenty five
non adherent patients had summary score between 5 and 8.
Comparison of variables with Adherence. The univariate analysis is presented in Table 2 and 3. Among the quantitative variables, monthly income of the patients was found to be significantly associated with adherence (p-value 0.015). Among the categorical variables, prevalence of depression (p value <0.000001), moderate severe depression (p<0.000001) and concomitant drug burden (p value = 0.036) were found to be significantly associated with adherence behaviour. Non depressed people were more likely to be adherent (84.4% vs 43.5%). Patients with no concomitant drug burden were more likely to be adherent (78.8% vs 53.3%).
|Table 2. Comparison of quantitative data with adherence|
|Table 3.Comparison of Categorical Variables with Adherence|
The results of the logistic regression
analysis of factors associated with adherence (9-MMAS summary score ≥
11), adjusted for covariates are presented in Table 4. The variables
included in the study were age, knowledge about medicine and treatment,
physician patient interaction, those who attended patient educational
sessions, male, depressed patients, smokers, alcoholics, educational
qualifications, employed patients, patients who had side effects, being
financially assisted in treatment, had concomitant drug burden, having
polypharmacy and dosage of imatinib. Full data were available for all
the 100 patients, who were included in the logistic regression
analysis. Prevalence of depression among CML patients remained
independently associated with adherence (OR= 10.367, 95% CI 3.112-
|Table 4. Multiple logistic regression analysis to identify the predictors of adherence|
Optimal adherence to imatinib therapy is crucial to maximize treatment effectiveness,[4,5,7,8] however the ability of the physician to recognize adherence is poor. Given the scanty data of CML literature, we selected the possible factors to be associated with the adherence behaviour based on previous studies in other chronic medical illnesses.[12,18,19,23] The percentage of patients found to be non-adherent in our study (i.e. 25%), seems consistent with previous data indicating non adherence rates of 25 to 50%. Also, it is difficult to make the comparisons regarding prevalence of non adherence in other studies as this fluctuates as a function of methods used. However, our study support previous findings that adherence to imatinib therapy is far from optimal (i.e 75 % of patients have adherence rates ≥ 95%) in CML patients. As per our knowledge, only one study in a small cohort of 38 patients have found ‘good’ adherence to imatinib therapy.
Negative significant association between the adherence and the prevalence of depression among the Indian CML cohort was observed with a p value <0.00001. 23% (n=23) of patients were found to be depressed, out of which none of the patient was severely depressed. 47.82 %(n=11), 34.78% (n=8) and 17.4% (n=4) patients were found to be mildly, moderately and moderately severely depressed. We further analyzed the severity (mild, moderate and moderately severe depression) of depression with adherence and found moderate severely depressed patients to be significantly associated with non-adherence (p<0.000001). Our study revealed that non depressed patients are more likely to be adherent (84.4% vs 43.5%). Prevalence of depression was found to be the only factor to be associated with adherence through multivariate logistic regression analysis with odds ratio of 10.367 with 95% confidence interval of odds ratio to be between 3.112 and 34.538. Given the paucity of data in the CML literature regarding the negative association between adherence and depression, our findings are thus consistent with the meta-analysis performed by Di Matteo et al which included 12 articles about depression and noncompliance to medical treatment and 13 articles about anxiety and noncompliance to medical treatment revealed a significant and substantial relationship between depression and non-adherence to medical treatment prescribed for chronic illnesses. A recent meta analysis on the depression and medication adherence of patients with chronic diseases in U.S population by Grenard et al estimated the odds of a depressed patient being non-adherent are 1.76 times the odds of a non-depressed patient across 31 studies and 18,245 participants.
In our cohort, concomitant drug burden was found to be negatively associated with adherence to imatinib therapy (p value – 0.036). Out of 15 patients on concomitant drugs, only 8 patients (53%) were found to be adherent. Though our results contrasts with the results obtained worldwide, which states that concomitant drug burden has a positive association with adherence to imatinib therapy in CML patients.[5,13] Noens et al showed an association between more medication to be taken daily and better adherence to imatinib therapy. A qualitative study by Eliasson et al  reported that adherent patients referred to taking imatinib as being part of their daily routine, possible to speculate that patients who are already taking medications for other diseases might be facilitating in fitting CML therapy into their regular overall medication taking schedule. However, we might have observed such a contrasting result because the concomitant drug burden in the previous studies was fairly high (41.16% in Efficace F et al) unlike our study (15%) and only 46% of the patients in the 9-MMAS reported that they had a special routine or a reminder system to facilitate their medication taking behaviour.
58% patients were found to be working in our cohort of Indian CML patients with a mean monthly income of Rs.20,912.93 (range Rs.550-2,00,000). Our results showed monthly income to be associated with adherence to imatinib therapy (p value- 0.015) through univariate analysis but this was found to be insignificant when logistic regression analysis was performed.
There is conflicting evidence in the literature whether age influences adherence in CML patients. A study of 87 patients by Marin et al, showed that younger patients have lower adherence rate whereas older patients with a median age of 53.8 years had an adherence rate of greater than or equal to 90%. Unlike our study, did not show that increasing age positively influences adherence (p value – 0.795).
A study of Darkow et al on 267 patients showed adherence to be influenced by gender, non adherence was significantly higher in women; in the present study this difference was not observed (p = 0.234). Santoleri et al concluded that frequency of dosing does not influence adherence to drug therapy. Though the imatinib is once a day dose, but patients prescribed 600mg/day or 800mg/day of imatinib were advised to take half the dose in morning and other half in evening to manage the gastric side effects. Similar results were obtained through this study (p value – 0.536). Imatinib therapy is prolonged and previous research has shown that adherence for long – term drug therapies are lower, often no more than 40-50%, but our study reflected no significant association between adherence and duration of prescription (months) of imatinib( p= 0.743). The side effects of imatinib are relatively mild, dyspepsia (21%) and edema (21%) was found to affect the CML patients the most. As these side effects are mild, adherence was found not to be influenced by side effects (p=0.051). Richardson et al showed that patient educational programs including information on disease and expected side effects were associated with better survival in patients with hematologic malignancies. Moon et al reported that a counselling programme was effective in improving compliance in CML patients receiving imatinib. But, our study did not reflected the similar results, as we found patient educational sessions did not play a significant role in influencing adherence (p value- 0.325)
Backward step wise multiple logistic regression analysis was used to find the independent predictors of adherence. Initially, all the independent variables were included in the model. Further, non-associated variables were dropped one by one step wise and finally age, knowledge about medicine and disease, physician patient interaction, patient educational sessions, prevalence of depression, financial assistance and concomitant drug burden were selected at 10th step with probability less than 30%. The criterion of 30% was based on the assumption to find the closely related variables with adherence. Among all the selected variables, only depression was significantly (OR 10.367; 95% C.I, 3.112- 34.538) associated with the adherence. However, other independent variables showed the closeness to the adherence. Marin et al showed that younger patients have lower adherence. In HIV patients, the perceived very good contact with health care was found to be associated with adherence to antiretroviral treatment. Efficace et al found concomitant drug burden as an independent predictor of adherence in CML patients to IM. Moon et al reported that a counselling programme was effective in improving compliance in CML patients receiving imatinib.
This paper has number of strengths including, selection bias is likely to be limited as the proportion of non-respondents was fairly small (15 of 115). A response rate of almost 87% is fairly good and the proportion of eligible patients was also high (115 of 139). No internal attrition was found. For appropriate results, the sample size approximation was priorly done in accordance with the adherence study conducted on Indian population.
This paper, however, also has potential limitations. First, we might have missed additional patient related and psychological factors that might have found to be related to adherence in patients with other diseases. Second, we used non validated questionnaire to assess the factors influencing adherence except depression and third, it is possible that additional measures of adherence could have further contributed to a more sensitive definition of adherence in our study. However, the methods available for measuring adherence all have different strengths and weaknesses; because of the complexity of the adherence behaviour and problems with bias, none is optimal and self-report methods provide a good estimation of medication adherence in an inexpensive manner over a possible breadth of distribution and also have great advantages over other methods.
These potential limitations notwithstanding, we are confident our results extend findings of previous research in the field of adherence and investigation of factors influencing adherence in CML on IM to suggest key potential determinant of adherence behaviour. Physicians are encouraged to pay attention to factors identified in this study could help to promptly identify patients who might be at a heightened risk of non adherence.
We thank Dr. Jes Rafael for his valuable suggestions to improve the design and conduct of the study. Dr. Tabassum, Dr. Shishir Seth played a vital role in helping to recruit the patients in the study. We would like to pay our gratitude to Dr. Ram Chandra Bajpai for performing the statistical analysis and critically reviewing the manuscript. We are indebted to Dr. Suman Pramanik for critical reading of the manuscript and Mrs. Niharika Bhatia, Miss Priyanka Shrivastav for the unconditional support in the conduct of the study. We thank all the members and staff of Rajiv Gandhi Cancer Institute and Research Centre, India.
- Druker BJ, Guilhot F, O' Brien SG et al. Five
year follow up of patients receiving imatinib for chronic myeloid
leukemia. N Eng J Med 2006; 355: 2408-2417.
HM, Cortes J, La Rosee P, Hochhaus A. Optimising therapy for patients
with chronic myelogenous leukemia in chronic phase. Cancer 2010; 116:
- Vrijens B, De Geest S, Hughes DA et al. A new taxonomy for describing and defining adherence to medications. Br J Clin Pharmacol 2012; 73: 691–705. http://dx.doi.org/10.1111/j.1365-2125.2012.04167.x PMid:22486599 PMCid:PMC3403197
- Marin D, Bazeos A, Mahon FX, Eliasson L, Milojkovic D, Blea M, Apperley JF, Syzdlo R et al. Adherence is the critical factor achieving molecular responses in patients with chronic myeloid leukemia who have achieve complete cytogenetic responses on imatinib. J Clin Oncol 2010; 28 : 2381 – 2388. http://dx.doi.org/10.1200/JCO.2009.26.3087 PMid:20385986
- Noens L, van Lierde MA, De Beck R et al. Prevalence, determinants, and outcome of non-adherence to imatinib therapy in patients with chronic myeloid leukemia : The ADAGIO Study. Blood 2009 ;113 : 5401 -5411. http://dx.doi.org/10.1182/blood-2008-12-196543 PMid:19349618
- DarkowT, Henk HJ, Thomas SK, et al. Treatment interruptions and non adherence with imatinib and associated healthcare costs : A retrospective analysis among managed care patients with chronic myelogenous leukemia. Pharmacoeconomics2007; 25 :481 -496. http://dx.doi.org/10.2165/00019053-200725060-00004 PMid:17523753
- Ibrahim AR, Eliasson L, Apperley JF, Milojkovic D, Bua M, Syzdlo R et al. Poor adherence is the main reason for loss of CCyR and imatinib failure for chronic myeloid leukemia patients on long term therapy. Blood 2011 ; 117 (14) : 3733 – 6. http://dx.doi.org/10.1182/blood-2010-10-309807 PMid:21346253
- Ganesan P, Sagar TG, Dubashi B, Rajendranath R, Kannan K, Cyriac S et al. Non adherence to imatinib adversely affects event free survival in chronic phase chronic myeloid leukemia. Am J Hematol.2011 ; 86 (6) :471 -4. http://dx.doi.org/10.1002/ajh.22019 PMid:21538468
- JonssonS, Olsson B, Soderberg J, Wadnenvik H. Good adherence to imatinib therapy among patients with chronic myeloid leukemia – a single center observational study. Ann Hematol 2012, 91 : 679- 685. http://dx.doi.org/10.1007/s00277-011-1359-0 PMid:22048790
Dos Reis S, de Souze Quixada A, Nune S, Camelocid MD, de Souza J, de
Costa C et al. Adherence to imatinib in chronic myeloid leukemia : a
study of first decade of responses obtained at a Brazilian Hospital.
Rev Bras Hematol Hemoter. 2013 35 (3) :174-9 .
- Ruddy K, Mayer E, Patridge A. Patient adherence and persistence with oral anticancer treatment. CA Cancer J Clin (2009), 59:56-66. http://dx.doi.org/10.3322/caac.20004 PMid:19147869
- Di Matteo MR. Social support and patient adherence to medical treatment : a meta- analysis. Health Psychol (2004), 23: 207-218. http://dx.doi.org/10.1037/0278-622.214.171.124 PMid:15008666
- Efficace F, Baccarani M, Rosti G et al. Investigating factors associated with adherence behaviour in patients with chronic myeloid leukemia: an observational patient-centered outcome study. Br J Cancer (2012),107 :904-909. http://dx.doi.org/10.1038/bjc.2012.348 PMid:22871884 PMCid:PMC3464760
- Sodergard B, Halvarsson M, Tully MP, Mindouri S, Nordstom ML, Lindback S, et al. Adherence to treatment in Swedish HIV – infected patients. J Clin Pharm Ther 2006, 31 : 605 – 616. http://dx.doi.org/10.1111/j.1365-2710.2006.00782.x PMid:17176366
- Morisky DE, Green LW, Levin DM. Concurrent and predictive validity of a self reported measure of medication adherence. Med Care 1986, 24 : 67-74. http://dx.doi.org/10.1097/00005650-198601000-00007 PMid:3945130
- Morisky DE, Ang A, Krousal – Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens2008, 10 : 348 – 354. http://dx.doi.org/10.1111/j.1751-7176.2008.07572.x
- Osterberg L, Blaschke T. Adherence to medication. N Engl J Med 2005, 353:487–497. http://dx.doi.org/10.1056/NEJMra050100 PMid:16079372
- Vermeire E, Hearnshaw H, Van Royen P, Denekens J. Patient adherence to treatment: three decades of research. A comprehensive review. J Clin Pharm Ther 2001, 26: 331–342. http://dx.doi.org/10.1046/j.1365-2710.2001.00363.x PMid:11679023
- Di Matteo MR. Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research. Med Care 2004, 42: 200–209 http://dx.doi.org/10.1097/01.mlr.0000114908.90348.f9 PMid:15076819
- Santoleri F, Sorice P, Lasala R, Rizzo CR, Constantini A. Patient adherence and persistence with imatinib, nilotinib, dasatinib in clinical practice. Plos One 2013, 8; issue 2. PMid:23437249 PMCid:PMC3577678
- Krousal Wood M, Hyre A, Muntner P, Morisky D. Methods to improve medication adherence in patients with hypertension: Current status and future directions. Curr Opi Cardiol 2005, 20 : 296 – 300.
- Dimatteo MR, Leeper HS, Croghan TW. Depression is a risk factor for non compliance with medical treatment :Meta-analysis of the effects of anxiety and depression on patient adherence. Archives of Internal Medicine 2000, 160 (14) : 210 -217. http://dx.doi.org/10.1001/archinte.160.14.2101
- Eliasson L, Clifford S, Barber N, Marin D. Exploring chronic myeloid leukemia patient's reasons for not adhering to the oral anticancer treatment drug imatinib as prescribed. Leuk Res 2011;35:626-630. http://dx.doi.org/10.1016/j.leukres.2010.10.017 PMid:21095002
- Grenard JL, Munjas BA, Adams JL, et al. Depression and medication adherence in the treatment of chronic diseases in the United States: A meta-analysis. Journal of General Internal Medicine. 2011;26:1175–1182. http://dx.doi.org/10.1007/s11606-011-1704-y PMid:21533823 PMCid:PMC3181287
- Markkula A, Hietala M, Henningson M, Ingvar C, Rose C, Jernstrom H (2012) Clinical profiles predict early nonadherence to adjuvant endocrine treatment in a prospective breast cancer cohort. Cancer Prev Res 5: 735–745 http://dx.doi.org/10.1158/1940-6207.CAPR-11-0442 PMid:22401981
- Richardson JL, Shelton DR, Krailo M, Levine AM (1990) The effect of compliance with treatment on survival among patients with hematologic malignancies. J Clin Oncol 8: 356–364 PMid:2299375
- Moon JH, Sohn SK, Kim SN, Park SY, Yoon SS, Kim IH, Kim HJ, Kim YK, Min YH, Cheong JW, Kim JS, Jung CW, Kim DH (2011) Patient counseling program to improve the compliance to imatinib in chronic myeloid leukemia patients. Med Oncol 29: 1179–1185. http://dx.doi.org/10.1007/s12032-011-9926-8 PMid:21472487
Metrics powered by PLOS ALM
Copyright (c) 2016 Mediterranean Journal of Hematology and Infectious Diseases
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.