Study design and setting
This trial is a single-centre, unblinded, randomized two-arm study with a nested qualitative study. A multiprofessional medication management (MuMM) intervention was implemented at an oncologic outpatient ward of the Johanniter-Hospital, a municipal hospital in Bonn, Germany, to assess its feasibility in clinical practice. The hospital does not have an own pharmacy, pharmaceutical services are provided by a community pharmacy.
The recruitment period was from November 2012 until January 2014. Patients were enrolled by the study team after signing written informed consent and the randomization was carried out in terms of a computer-generated block randomization with variable block size by a staff member not involved in the study. Because of the nature of the intervention, including repeated medication reviews and counseling, patients and medical staff could not be blinded. Data collection and assessment were not blinded either. Patients were observed for a maximum of five chemotherapy cycles. The sample size was set to 50 patients aiming at evaluating the feasibility of a full-scale efficacy study.
Participants
Eligible patients were randomized 1:1 either to the control group receiving standard care, or to the intervention group receiving the MuMM intervention. Inclusion criteria required that patients were age 18 or older, had been diagnosed with a solid tumor, were receiving anticancer drug therapy, and were able to speak, read and write German. Exclusion criteria included a diagnosis of a hematologic malignancy, the presence of comorbid conditions (e.g. Alzheimer’s disease) that would preclude the ability to provide informed consent or limit comprehension of the patient-reported outcome measures and the intention to change the location of treatment in the near future.
Intervention development
To develop a structured and standardized medication management for a multiprofessional team of physicians, nurses, and pharmacists, the current evidence on medication management and supportive care was searched by a detailed literature review. The medication management process was based on a modular approach. Hence, different care modules were developed including a basic care module and four supplementary modules. The basic care module corresponds to the core components of a medication management. These are a comprehensive medication review including an interaction check and the identification of drug-related problems, patient counseling on their medication, and the provision of a written medication plan. A prescreening for chemotherapy-induced toxicity is also part of the basic care module. The four supplementary modules comprise the management of the common adverse drug reactions nausea/vomiting, mucositis, fatigue, and pain. Each supplementary module consists of a bundle of measures on three different levels of the medication process: (1) the therapy, (2) the patient, and (3) the health care providers. The therapy level is addressed by written evidence-based recommendations for supportive therapy of the corresponding toxicity. At the patient level written leaflets for patient information and counseling on prevention and therapy of the corresponding symptoms are to support the patient in taking a more active role. And finally, the level of the health care providers is addressed by care algorithms illustrating every step of the care process and defining and allocating tasks and responsibilities to the different members of the multiprofessional care team (see Figure 1 for the structure of the MuMM intervention). The individual modules were discussed and finalized in several meetings consisting of at least one physician, one pharmacist, and one nurse.
Study intervention
Patients in the control arm received standard care according to the current practice in Germany where pharmacists usually (and especially in the study centre) do not act at the bedside and do not have direct contact to patients on the ward. Moreover, structured exchange and communication between physicians, pharmacists and nurses regarding medication safety are not common so far.
Participants randomized to the intervention arm received the modular MuMM intervention. After the randomization to the intervention group the basic care module was applied to every patient by the study pharmacist. Within a patient interview, a comprehensive medication reconciliation was conducted and the patient was informed and counseled in detail regarding his or her therapy and possible adverse drug reactions. Subsequent to the patient interview, a medication review focusing on drug-drug interactions was conducted, and a written medication plan was compiled. In case of identified medication-related interactions, the medication was adjusted in collaboration with the responsible physician. The basic module was applied by the study pharmacist after patient inclusion and at the beginning of every new cycle until the fifth cycle of chemotherapy. In the case that patients showed symptoms like nausea/vomiting, mucositis, fatigue or pain, the corresponding supplementary modules were initiated by the pharmacist (see Figure 2 for the course of the intervention). The modules for nausea/vomiting and mucositis were also initiated if the chemotherapy had a low to high emetogenic risk or the patient had a risk >10% to develop severe mucositis, respectively. All supplementary modules included the evidence-based supportive therapy for the corresponding adverse drug reaction in close cooperation between all health care professions as well as patient counseling with regard to non-pharmacological and pharmacological self-care measures to prevent or alleviate symptoms. Patient counseling was supported by the provision of written information and documentation material in terms of information booklets. The algorithms of the supplementary modules are provided as supplementary information (Suppl. 2-5).
Feasibility assessment
The feasibility of the intervention by the different health care providers was assessed by analyzing the application of the different care modules, i.e. the frequency of patient counseling within the basic care module, the extent of delivery of written medication plans, the number of patients with active modules, and the number of applied modules per patient.
Moreover, the experience gained by the clinical staff after implementation of the MuMM intervention was evaluated by means of semi-structured interviews with open questions. Hence, questions were prespecified but changes in sequence and formulation as well as further enquiry were allowed. The interviews were recorded, transcribed, and the main statements of the participants categorized and coded by intuitive coding according to a qualitative content analysis with the Software MAXQDA 11 (VERBI GmbH, Berlin).
Outcome measures
Symptom burden
Symptom burden was defined as primary outcome and assessed according to the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAETM) of the National Cancer Institute (NCI), USA [17]. The PRO-CTCAE item library includes items that capture the full range of symptomatic treatment effects that may be experienced across a variety of disease sites and cancer treatment modalities [18, 19]. It was validated in a large population of cancer patients in the USA [20].
A set of 31 items drawn from the translated German PRO-CTCAE item library has been evaluated concerning its quantitative measurement properties [21]. Out of the validated German PRO-CTCAE item set 19 items were selected for this study. 11 out of these 19 items focusing on the five anticancer treatment-related symptoms nausea, vomiting, mucositis, fatigue, and pain, were further analyzed as they were directly targeted by the four supplementary modules of the intervention. The recall period was the past seven days. Symptom burden was assessed after randomization (cycle 0) and at the beginning of every new cycle for a maximum of five cycles (cycle 1 to 5).
Health-related quality of life and patient satisfaction with information
Further secondary outcomes were health-related quality of life (HRQoL) and patient satisfaction with the received information. Health-related quality of life was assessed with the global health status scale of the QLQ-C30 V 3.0 questionnaire from the European Organization for Research and Treatment of Cancer (EORTC). The QLQ-C30 is a validated questionnaire particularly developed for cancer patients [22]. HRQoL of the patients was assessed after randomization and before first treatment (cycle 0) and at the beginning of every new treatment cycle retrospectively for the last 7 days for a maximum of five cycles (cycle 1 to 5).
The satisfaction of patients with the information about their disease and treatment was assessed with the validated German version of the Patient Satisfaction with Cancer Treatment Education Questionnaire (PS-CaTE) [23]. The questionnaire consists of four subscales assessing satisfaction with information on cancer treatment, adverse effects, complementary treatment options, and information sources. Overall satisfaction with cancer treatment education is computed as the mean of all subscales; the theoretical score range is 1 to 5, with higher scores indicating greater satisfaction [23]. Patient satisfaction with information was assessed after randomization and at the end of cycle 5 or at the patient’s last treatment cycle if he or she received less than five cycles of chemotherapy.
Statistical analysis
The original study protocol aimed at evaluating the influence of the MuMM intervention on the proportion of patients suffering from at least one severe symptomatic toxicity as primary outcome. A formal sample size calculation was performed resulting in a number of 74 patients based on an assumed reduction of the primary outcome by 50%, a significance level of 5%, a power of 80%, and a drop-out rate of 20%. However, the planned sample size could not be reached due to termination of the recruitment period. In order to allow the full exploitation of the information content of the data from the 51 available patients we decided to extend the analysis of the primary outcome and evaluated the time-dependence of symptom burden using generalized estimating equation (GEE) models for each symptom targeted by the intervention.
For this purpose, scores for PRO-CTCAE item clusters were calculated per cycle according to the following equations. The composite PRO-CTCAE item clusters are specified in Table 1. The raw score (RS) was formed by the average of the items I1,2,…,n that contribute to a cluster:
The scores for PRO-CTCAE item clusters were standardized by a linear transformation to a scale from 0 to 100 according to Equation 2 with higher scores indicating a higher symptom burden:
where range refers to the difference between the maximum possible value and the minimum possible value of the answer options. In cases of missing data, scores for PRO-CTCAE item clusters were calculated if at least 50% of the item values were available [21].
Data entry and statistical data analysis were carried out using ExcelTM 2007 (Microsoft, Redmond, Washington, USA), SPSS, version 22 (SPSS Inc., Chicago, Illinois, USA), SAS, version 9.3 (SAS Institute Inc., Cary, North Carolina, USA), and R, version 3.3.3 [24]. Descriptive statistics (means, standard deviations, medians, ranges, counts, percentages) was used to characterize the patient population and summarize the study results. The level of significance was set to 5% (p < 0.05) for all analyses.
Table 1: PRO-CTCAE item clusters for symptom terms
Item cluster
|
Number of items
|
Item dimensions
|
|
Nausea
|
2
|
Frequencya, severityb
|
|
Vomiting
|
2
|
Frequencya, severityb
|
|
Mucositis
|
2
|
Severityb, interferencec
|
|
Fatigue
|
2
|
Severityb, interferencec
|
|
Pain
|
3
|
Frequencya, severityb, interferencec
|
|
aScore range from ‘never’ (0) to ‘almost constantly’ (4); bScore range from ‘none’ (0) to ‘very severe’ (4); cScore range from ‘not at all’ (0) to ‘very much’ (4)
Repeated measures of symptom scores (nausea, vomiting, mucositis, fatigue, pain) formed according to equations 1 and 2 were used as dependent variables in the GEE models. Covariates included in the analysis were treatment group, therapy cycle, and treatment modification (yes/no, defined by dose reductions, dose delays, adjustments of therapy, or discontinuation of therapy). Generalized score tests were used to analyze the effects of covariates on symptom scores. For each symptom score a separate model was fitted.