BACKGROUND. ImRx for CML is a long-term treatment. Patterns and prevalence of NA to ImRx remain largely unknown. Short-term NA trends may be indicative of long-term NA. Methods for clinical NA assessment vary in reliability. A multimethod approach is indicated. OBJECTIVE. Multimethod estimation of patterns and prevalence of ImRx NA in CML pts at baseline (BL) and follow-up (FU) at 90 days (90d), incl. BL to 90d changes. DESIGN AND PATIENTS. Data subset from prospective, 90d observational, open-label, multicenter study. 169 evaluable pts on ImRx for minimum 30d at enrollment [1]. METHODS OF NA ASSESSMENT. At BL (NA with prior ImRx) and 90d (NA during study): visual analog scale (VAS) for physicians (phs; mVAS), pts (pVAS), cos (cVAS); Basel Assessment of Adherence Scale for pts (pBAAS; structured interview re NA in past 4 weeks [4wks]); pts reported persistence (pPST); % clinic appointments (%CAPPTS) kept (if any scheduled). At 90d also: % of ImRx taken per pill count (%pts@ImRx). RESULTS. See Table 1. CONCLUSIONS. Intuitive adherence ratings (VAS) by phs, pts, and cos are very high and differ from those from structured interview, where about one-third of patients exhibited NA behavior in 4wks prior to BL and FU - despite high persistence. Pill count suggests patterns of under- and overtaking, with only 1 out 7 patients being perfectly adherent. Rate of clinic appointments may be affected by physician scheduling practices and collateral input is a function of availability of collateral person. Consenting to participate in the ADAGIO study did not reduce NA. Though patient self-reports in structured interview (pBAAS) and pill counts have inherent biases, both indices suggest that NA with ImRx may be similar to NA rates in other disease categories. Especially pBAAS and pill count may be useful rapid clinical assessment tools, with pBAAS having the benefit of validated categorical assessment (vs. continuous in other methods). Determinants of NA and the impact of NA on treatment outcomes must be examined. Table 1 - Multimethod Assessment of Non-Adherence with Imatinib Method BL 90d n M±SD/Min-Max M±SD/Min-Max P mVAS 164 95.0±7.6/60–100 94.9±9.9/0–100 ns pVAS 169 95.3±8.5/25–100 95.7±6.1/75–100 ns cVAS 56 97.1±5.1/80–100 97.4±5.1/75–100 ns %pts@ImRx 162 - 91.0±21.1/29.5–2002.2 71.0% @ < 100% ImRx 14.2% @ 100% ImRx n % NA % NA P pBAAS 163 36.2% 32.5% ns %CAPPTS 51 94.1% 88.2% 0.001 pPST 163 98.8% 100.0% ns

BACKGROUND. ImRx for CML is a long-term treatment potentially compromised by NA. Identifying APVs may assist in reducing NA and optimizing treatment outcomes. OBJECTIVE. To model the relationships between two NA measures and selected APVs using CCA, a multivariate analog of multiple regression to accommodate multiple criterion variables. DESIGN AND PATIENTS. Data subset from prospective, 90d observational, open-label, multicenter study. 169 evaluable pts on ImRx for minimum 30d at enrollment [1]. MEASUREMENTS. NA at 90d vector: Basel Assessment of Adherence Scale for pts (pBAAS; 0/1 with 1=NA); and % of ImRx taken per pill count (%ImRx, subtracted from 100 to reflect NA). APVs at BL vector: age; months since CML diagnosis (mCML); months since ImRx initiation (mImRx); knowledge of CML disease, treatment, and ImRx (KCMLRx); and general health (SF-8). RESULTS. The criterion (dependent) vector of NA indicators included pBAAS and %ImRX. The predictor (independent) vector of APVs included: age, mCML, mImRx, KCMLRx, and SF-8. Two canonical correlations were generated: 0.389 (Bartlett Chi-squared=23.564, P=0.009) and 0.170 (Bartlett Chi-squared= 3.590, P=0.464); the second correlation was deleted due to nonsignificance from zero. The canonical loadings (or structure coefficients) for the retained model were: age 0.951, mCML 0.205, mImRx 0.145, SF-8 0.016, and KCMLRx -0.367. Redundancy analysis showed that 22.1% of variance in the predictor set was explained by variables within that set. CONCLUSIONS. The patient NA vector (composed of a binary assessment of NA per pBAAS 0/1 with 1=NA) and continuous quantification of % of ImRx not taken was related to the APV vector as follows: NA increased as patients were older, had been diagnosed with CML for a longer period of time, had been on imatinib treatment for a longer period time, and were in slightly better health at enrollment. These may be considered warning signs for NA for clinicians to consider in practice, given the long-term nature of ImRx. Importantly, better patient knowledge of disease and treatment, a clinically modifiable APV, was associated with a decrease in NA. The initial insights in patient NA with ImRX provided by these findings, though some are counterintuitive to the NA literature at large, must be studied further to better understand the dynamics of NA in the CML population.

BACKGROUND. Patterns, prevalence, and associated pt variables of CML pts’ nonadherence (PNA) with ImRx are being better understood. Reducing ImRx PNA may impact on treatment outcomes. Various AESs have been proposed but their perceived value and clinical applicability to treating MDs are unknown. OBJECTIVES. 1. Describe the perceptions of ImRx prescribing MDs of the utility (in terms of FX, FB, CO) of 13 AESs. 2. Describe MD rankings of the applicability in daily practice of each AES. DESIGN AND SUBJECTS. MD data subset from prospective, 90d observational, open-label, multicenter study [1]. 51 evaluable MDs: age 45.6±11.2 years (ys); ys of practice 17.7±8.1; 74% hematologists, 26% oncologists; 65.3% practicing in university(-affiliated) hospital, 34.7% in other hospitals. MEASUREMENTS. Utility rated 0=none to 3=high. For applicability to daily practice, MDs were asked to give top 5 AESs (5=most applicable); nonranked AESs were given zero value. RESULTS. See Table 1. CONCLUSIONS. MDs tended to rate the utility and applicability of AESs higher if an AES involved active MD participation or decision-making. AESs requiring significant patient involvement, behaviorally or through assistive devices, were perceived as less helpful and applicable in clinical practice. Importantly, the critical role of patient education was recognized, thus challenging clinicians to accept greater responsibility for this AES. Nurses in particular may prove pivotal in patient education. These findings provide significant direction for interdisciplinary healthcare education, especially in terms of chronic illness management. Further research is needed to elucidate the physician-centric approach to adherence enhancement in CML pts on ImRx. Table 1 - Physician Utility Ratings and Applicability Rankings of Adherence-Enhancing Strategies Utility (0–3) Applicability FX FB CO in Practice (0–5) M±SD M±SD M±SD M±SD Rx selection per pt characteristics 1.9±1.1 1.6±1.1 1.3±1.0 1.0±1.5 Pt education 2.6±0.6 2.1±0.8 1.4±0.8 3.1±1.9 Improved pt-MD communication 2.7±0.5 2.3±0.8 1.3±0.8 2.8±1.7 Simplifying Rx regimen 2.5±0.7 2.3±0.7 1.6±0.9 2.3±1.9 Pt self-monitoring 1.7±0.8 1.5±0.8 1.1±0.9 0.4±1.1 Pt health status diary 1.7±0.8 1.5±0.8 1.0±0.8 0.5±1.3 Memory aids 1.7±0.8 1.9±0.8 1.0±0.8 0.6±1.3 Spouse/family involved 2.2±0.9 2.0±0.9 0.6±0.8 1.3±1.4 Regular MD contact 2.4±0.5 2.2±0.7 1.7±0.8 2.2±1.8 MD monitoring of PA 2.2±0.7 1.8±0.9 1.4±0.8 0.7±1.1 Electronic reminders 1.5±0.9 1.2±0.8 2.3±0.9 0.3±1.1 Electronic Rx monitoring 1.6±0.9 1.3±0.7 2.3±0.9 0.3±1.1 Rewards for good PA 1.4±1.0 1.3±0.8 1.8±0.9 0.5±1.4