Pharmacist-led interventions in hematological malignancies: a systematic review of clinical, process and economic outcomes.

Introduction

Hematological malignancies, including leukemia, lymphoma, and multiple myeloma (MM), involve complex pharmacotherapy regimens characterized by high treatment intensity, narrow therapeutic indices, frequent dose modifications, and considerable toxicity risks ( Sochacka-Ćwikła et al., 2021 ). Over the past decade, the field has undergone rapid therapeutic innovation, with the introduction of targeted therapies, monoclonal antibodies, bispecific antibodies, and cellular therapies that have transformed treatment approaches ( Sochacka-Ćwikła et al., 2021 ; Tang et al., 2023 ; Hou et al., 2021 ). While these advances have expanded therapeutic options and improved outcomes, they have also increased the complexity of care delivery and medication management.

Compared with many solid tumors, hematological malignancies often require urgent treatment initiation, intensive laboratory monitoring, and highly individualized dose adjustments. Patients frequently receive profoundly immunosuppressive regimens associated with severe myelosuppression and a substantial risk of infection during neutropenic periods, necessitating close monitoring and proactive supportive care ( Howell et al., 2022 ; Nucci and Anaissie, 2017 ). In addition, many modern hematologic therapies introduce distinct toxicity profiles and specialized monitoring requirements; for example, chimeric antigen receptor T-cell (CAR-T) therapies and bispecific antibodies require close monitoring for immune-mediated toxicities such as cytokine release syndrome and neurotoxicity, whereas targeted agents such as Bruton tyrosine kinase inhibitors and BCL-2 inhibitors necessitate careful dose optimization and monitoring for complications including cytopenias, tumor lysis syndrome, and cardiovascular adverse events (AEs) ( Hou et al., 2021 ; Markouli et al., 2023 ).

Pharmacists, particularly in oncology and hematology practice, are well positioned to address these challenges through pharmacist-led interventions that support medication optimization, toxicity monitoring, adherence support, and patient education ( Banez et al., 2024 ; Siddiqui et al., 2023 ; Ochs et al., 2022 ). In broader oncology populations, such interventions have been associated with improvements in medication safety and treatment outcomes. For example, an integrated pharmacist-led oral chemotherapy management program reported by Muluneh et al. involving 367 patients demonstrated a substantial improvement in adherence to oral anticancer therapy, with adherence rates increasing from 74% prior to program implementation to 96% following pharmacist-led management, alongside improved clinical outcomes and earlier identification of treatment-related toxicities ( Colombo et al., 2017 ). Other studies in mixed oncology populations have similarly reported reductions in medication errors, enhanced adverse drug event (ADE) monitoring, and improvements in patient-reported outcomes (PROs) such as quality of life (QoL) and treatment satisfaction ( Xiang et al., 2025 ; Fentie et al., 2025 ).

However, the current evidence base on pharmacist-led interventions in oncology is largely derived from mixed cancer populations in which outcomes are predominantly driven by patients with solid tumors. Previous systematic reviews have therefore primarily evaluated care models and outcomes relevant to solid tumor management ( Colombo et al., 2017 ; Xiang et al., 2025 ; Fentie et al., 2025 ). As a result, the applicability of these findings to hematological malignancies remains uncertain, given the distinctive clinical characteristics, treatment intensity, and supportive care requirements associated with hematologic cancers.

Furthermore, existing reviews frequently report heterogeneous outcome measures, apply inconsistent definitions of pharmacist interventions, and evaluate pharmacist activities as part of broader multidisciplinary care models, making it difficult to isolate the specific contribution of pharmacist-led services ( Chung et al., 2019 ).

This systematic review is the first to focus exclusively on pharmacist-led interventions in hematological malignancies, thereby addressing gaps left by previous oncology-focused reviews. In addition, it captures real-world service models beyond randomized trials, integrating clinical, process-related, and economic outcomes, supported by a formal risk-of-bias appraisal. Economic outcomes were included to reflect real-world service evaluation and health-system priorities, despite anticipated methodological heterogeneity in economic reporting. This review seeks to determine whether, in patients with hematological malignancies receiving systemic anticancer therapy, pharmacist-led medication management interventions (compared with usual or non-pharmacist-led care) improve medication adherence and safety outcomes.

By thoroughly assessing both the strengths and limitations of the current evidence base, this review aims to support service development, inform policy decisions, and guide future research efforts to enhance care for this high-risk patient population.

Methods

Study design

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines ( Page et al., 2021 ). The PRISMA checklist is provided in the Supplementary Material ( Supplementary Table S1 ). The research question was defined using the Population, Intervention, Comparator, Outcomes, and Study Design (PICOS) framework ( Table 1 ). The review protocol was prospectively registered in the PROSPERO database (registration ID: CRD420251147239).

Studies were included if they met the following criteria: (1) participants of any age diagnosed with hematological malignancies; (2) pharmacist-led interventions specifically aimed at optimizing hematology-oncology pharmacotherapy, including but not limited to prescribing oversight, therapeutic drug monitoring (TDM), medication reconciliation, formulary management, dose adjustment, patient education or counseling, and implementation of clinical guidelines; and (3) reporting of at least one relevant outcome, categorized as clinical, process-related, or economic (further details described in Section 3.6).

Eligible study designs included randomized controlled trials (RCTs), prospective and retrospective cohort studies, case-control studies, quasi-experimental and pre-post interventional studies, pilot or implementation studies, and other observational designs conducted in hospital or ambulatory care settings. Due to the limited number of controlled trials exclusively assessing pharmacist-led interventions in hematological malignancies, studies without explicit comparators, such as single-arm pre-post or descriptive implementation studies, were also included to reflect real-world practice and service delivery models. These uncontrolled designs were included for descriptive synthesis rather than causal inference, and their findings were interpreted with appropriate caution. Findings from these studies were interpreted with appropriate caution. Only full-text articles published in English were considered to ensure consistent data extraction and methodological quality assessment.

Studies were excluded if they did not involve patients with hematological malignancies, if they focused solely on palliative or end-of-life care where disease-modifying therapy was not the main objective, or if they described pharmacist activities not related to optimizing hematology-oncology treatment or lacking a clearly defined clinical role. Review articles, editorials, commentaries, and conference abstracts were also excluded from this review.

Studies that included mixed cancer populations were deemed eligible only if outcomes specific to hematological malignancies were explicitly reported or could be reliably determined through subgroup analyses, tables, or Supplementary Material. Studies were excluded if hematology-specific outcomes could not be confirmed. Inclusion in the final synthesis was limited to studies that provided sufficient outcome data and methodological detail to allow for meaningful interpretation.

Data sources and search strategy

A systematic literature search was conducted in PubMed, Scopus, and Web of Science from inception to 1 August 2025. Search terms included variations of three core concepts: pharmacists (“pharmacist,” “clinical pharmacy,” “pharmacist-led,” “pharmacy-led,” “medication management”), hematological malignancies (“hematologic neoplasms,” “leukemia,” “lymphoma,” “myeloma,” “blood cancer”), and interventions (“intervention,” “optimization,” “stewardship,” “prescribing support,” “medication review,” “clinical service,” “treatment adherence”). Boolean operators (AND/OR) were applied, and search syntax was adapted for each database. The full search strategy for PubMed is presented in the Supplementary Material ( Supplementary Table S2 ). Reference lists of included studies were manually screened to capture additional eligible records.

Study selection

All records were imported into Zotero for de-duplication. Two reviewers independently screened titles and abstracts against the eligibility criteria, followed by full-text assessment of potentially relevant studies. Disagreements at both screening stages were resolved through discussion and consensus between the two reviewers; when consensus could not be reached, a third reviewer adjudicated the decision. Most disagreements were resolved at the discussion stage without the need for arbitration.

Data extraction

A standardized extraction form was developed and pilot tested. Extracted data included: study identification (ID, author, year, title, journal, database); screening status (inclusion in full-text review, inclusion in final review, reason for exclusion if applicable); study characteristics (design, country); participant details; intervention description; pharmacist role; comparator (if any); outcomes assessed; key findings; and risk of bias score.

Corresponding authors were contacted when full texts were unavailable or when additional data were required ( e.g ., hematology-specific results from studies reporting combined solid and hematological outcomes). No imputation was performed for missing data.

Data analysis and risk of bias assessment

A structured qualitative synthesis was performed, grouping findings into clinical, process-related, and economic outcomes. Meta-analysis was not undertaken due to heterogeneity in study design, intervention components, outcome definitions, and measurement methods, which precluded meaningful quantitative pooling.

Although no single primary outcome was prespecified, outcomes were interpreted with greater emphasis on those most consistently reported across studies. Studies were also described by design and intervention types to explore sources of heterogeneity.

Risk of bias was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklists, matched to study design: RCTs (13 items), cohort studies (11 items), case-control studies (10 items), analytical cross-sectional studies (8 items), quasi-experimental studies (9 items), case series (10 items), and economic evaluations (11 items) ( Joanna Briggs Institute, 2017a ; Hilton, 2024 ; Joanna Briggs Institute, 2017b ; Joanna Briggs Institute, 2017c ; Joanna Briggs Institute, 2017d ; Munn et al., 2019 ; Joanna Briggs Institute, 2020a ; Joanna Briggs Institute, 2020b ). These tools were selected a priori because the review included multiple study designs, and the JBI framework provides design-specific appraisal checklists that can be applied consistently across heterogeneous evidence bases, including quasi-experimental and economic evaluation studies. For studies reporting both clinical and economic outcomes, separate checklists were applied. Each “yes” response received one point. As the JBI tools do not provide standardized cut-off values for overall risk of bias, percentage scores were calculated and studies were classified as low (≥70%), moderate (50%–69%), or high (<50%) risk of bias, consistent with previous JBI-based systematic reviews ( Munn et al., 2019 ; McMenamin et al., 2023 ).

Outcome definitions and operational framework

Outcomes were categorized into three main domains: clinical, process-related, and economic; as detailed in Table 2 . Clinical outcomes focused on patient health effects, process outcomes on quality and efficiency of care, and economic outcomes on financial and resource impacts, with representative measures provided for each domain.

To note, hospitalization-related outcomes were classified as clinical when reported as safety or toxicity endpoints, and as economic outcomes when analyzed in terms of healthcare utilization or cost impact. When reporting economic outcomes, all “$” denotes USD unless otherwise stated.

Results

Study selection

A total of 243 records were identified through database searches: PubMed ( n = 33), Scopus ( n = 158), and Web of Science ( n = 52). After de-duplication, 197 unique records remained. Title and abstract screening excluded 87 records, leaving 110 articles for full-text review. Of these, 31 met the inclusion criteria. Manual reference screening identified an additional two studies, resulting in 33 articles included in the final review. Authors of potentially eligible studies were contacted to request missing full texts or hematology-specific data, but no additional information was obtained.

The study selection process is illustrated in the PRISMA flow diagram ( Figure 1 ).

Study characteristics

The 33 included studies, published between 2008 and 2025, were conducted across 12 countries. Study designs were heterogeneous, with non-randomized designs predominating. Quasi-experimental studies were most common ( n = 15, 45.5%), followed by prospective observational studies ( n = 6, 18.2%) and cohort studies ( n = 4, 12.1%). Retrospective observational designs were reported in two studies (6.1%), while the remaining designs were each reported in a single study.

Sample sizes ranged from 22 to 1,820 participants. Most studies focused on adults with hematological malignancies, particularly MM ( n = 9, 26.5%), chronic myeloid leukemia ( n = 7, 20.6%), and chronic lymphocytic leukemia ( n = 4, 11.8%). Three studies (8.8%) included mixed cancer cohorts but reported hematology-specific outcomes separately.

Pharmacist-led interventions were grouped into three non-mutually exclusive categories, as several studies reported multiple intervention components. Medication review and optimization was the most common intervention type ( n = 23, 69.7%). Patient education, counseling, and adherence support were reported in 22 studies (66.7%). Clinical and service integration was described in 14 studies (41.2%).

Comparators also varied. Twelve studies (35.3%) were single-arm evaluations without a comparator. Eleven (32.4%) used pre-intervention baselines. Five (15.2%) compared outcomes with historical, retrospective, or concurrent usual-care cohorts. Three (8.8%) reported active comparators, such as traditional physician-managed clinics or patients receiving identical monitoring tools without pharmacist follow-up. Two (5.9%) used risk-stratified or within-patient comparisons. A detailed overview of study characteristics is provided in Table 3 .

Risk of bias assessment

Risk of bias was assessed using the JBI critical appraisal checklists matched to each study design. Two studies (Zerbit et al. ( Zerbit et al., 2022 ) and Nguyen et al. ( Nguyen, 2023 )) underwent dual appraisal for observational and economic components, resulting in a total of 35 individual assessments. Of these, 19 (54.3%) were rated as low risk, 10 (28.6%) as moderate risk, and 6 (17.1%) as high risk. Figure 2 summarizes the distribution of risk of bias across included studies.

Synthesis of findings

Across the 33 included studies, 24 reported clinical outcomes, 23 reported process-related outcomes, and 8 reported economic outcomes. Several studies reported outcomes across more than one domain.

Clinical outcomes

Clinical outcomes were reported in 24 studies (72.7%). Medication adherence and persistence were evaluated in 9 studies (37.5%). Several studies reported improved adherence following pharmacist involvement, including increases from 86.5% to 93.6% ( p = 0.0007) and from 40.5% to 70.4% ( p = 0.0115) among patients receiving oral anticancer therapies ( Santoleri et al., 2019 ; Zanetti et al., 2023 ). Adherence exceeding 90% was achieved in 95% of patients receiving pharmacist-supported care compared with 73.6% in a historical cohort ( p = 0.029) ( Muluneh et al., 2018 ), and pharmacist monitoring was also associated with significantly higher adherence in another study ( p = 0.0135) ( Moulin et al., 2017 ). However, improvements were not consistently statistically significant across all studies; for example, adherence rates of 99% versus 92% in pharmacist-managed versus physician-managed care did not reach statistical significance ( p = 0.15) ( Zerbit et al., 2020 ). Other studies reported high adherence levels or identified non-adherence as a drug-related problem (DRP) without comparative analysis ( Périchou et al., 2020 ; Mansour et al., 2024 ).

AEs and treatment-related toxicities were reported in 14 studies (58.3%). Reductions in severe toxicities were observed in some settings, including lower rates of grade ≥3 AEs (8% vs. 15%) ( Zerbit et al., 2020 ) and grade 3-4 toxicities (26% vs. 38%, p = 0.001) ( Devaux et al., 2022 ). Pharmacist-led TDM in transplant populations was also associated with fewer early post-transplant AEs (11 vs. 20 at day +30, p = 0.03) ( Gawedzki and Collins, 2021 ). Several studies primarily reported the identification or management of adverse drug reactions (ADRs) within DRP assessments rather than demonstrating reductions in toxicity incidence ( Tan et al., 2021 ; Farias et al., 2016 ; Albayrak and Özbalci, 2024 ; Prot-Labarthe et al., 2008 ). Within a similar context, treatment interruptions or discontinuations were reported in 4 studies (16.6%). AEs contributed to 36% of treatment discontinuations and 72% of therapy switches in one monitoring program ( Wyatt et al., 2025 ), while pharmacist review resulted in discontinuation of unjustified prescriptions in 39% of cases in another study ( de Grégori et al., 2020 ). On the other hand, pharmacist involvement was associated with longer time to treatment failure in one comparative study ( p = 0.0005) ( Zerbit et al., 2020 ).

Disease response, survival outcomes, and PROs were assessed in 13 studies (54.2%), with mixed findings. Improved progression-free survival ( p = 0.002) and overall survival ( p = 0.004) were reported in one comparative study ( Zerbit et al., 2020 ), while increased molecular remission rates were observed among patients with chronic myeloid leukemia receiving pharmacist monitoring ( Moulin et al., 2017 ). Improvements in PROs, including QoL and psychological coping scores, were also reported ( Knight et al., 2022 ; Opsomer et al., 2016 ). However, several studies reported neutral findings. For example, improvements in major molecular response did not reach statistical significance ( p = 0.0575) despite improved early molecular response in one study ( Muluneh et al., 2018 ), and transplant mortality was similar between intervention and control groups in another study ( p = 0.8029) ( Zanetti et al., 2023 ).

Outcomes related to therapeutic drug exposure or dose intensity were reported in 5 studies (20.8%). High rates of target dose achievement were observed during venetoclax ramp-up protocols (94.3%) ( de Boer et al., 2025 ), and monitored cohorts maintained high relative dose intensity (mean 93.7%) ( Larbre et al., 2025 ). However, implementation of TDM protocols did not consistently improve drug concentration targets, with no difference in tacrolimus therapeutic levels observed at day +100 in one study ( Gawedzki and Collins, 2021 ).

Hospitalization-related outcomes were reported in 3 studies (12.5%). One study documented unplanned admissions in 5.7% of patients during venetoclax ramp-up ( de Boer et al., 2025 ), while another observed fewer rehospitalizations following pharmacist intervention, although this difference was not statistically significant ( p = 0.217) ( Devaux et al., 2022 ). Similarly, transplant readmission rates did not differ significantly between intervention and control groups in another study ( p = 0.5006) ( Zanetti et al., 2023 ).

While pharmacist involvement was frequently associated with improvements in adherence, toxicity management, and PROs, findings across clinical outcomes were heterogeneous, with both statistically significant benefits and neutral results reported across studies. Table 4 summarizes the clinical outcomes reported across included studies.

Process-related outcomes

Process-related outcomes were reported in 23 studies (69.7%). Identification and resolution of DRPs or drug-drug interactions (DDIs) were reported in 10 studies (43.5%). Pharmacists identified a broad range of medication-related issues, including dosing errors, ADRs, drug interactions, and monitoring gaps. Several studies reported high resolution rates following pharmacist intervention, including resolution of 77.3% and 78.9% of identified DRPs in two studies ( Tan et al., 2021 ; Albayrak and Özbalci, 2024 ). Another study reported a significant reduction in DDIs after implementation of pharmacist-led medication review, with an 81% decrease after 1 month ( p < 0.0001) ( Zerbit et al., 2020 ).

Pharmacist intervention frequency was reported in 17 studies (73.9%). The number of interventions ranged from 104 to 1,970 per study, depending on study design and population ( Albayrak and Özbalci, 2024 ; de Grégori et al., 2020 ). Several studies reported marked increases in intervention activity following the introduction of pharmacist services. For example, implementation of a ward-based clinical pharmacist increased the intervention rate from 0.34% to 1.87% of prescriptions ( p < 0.00001) ( Chen et al., 2020 ), while another study reported over 1,600 pharmacist interventions during chemotherapy management ( Ali et al., 2021 ).

Acceptance of pharmacist recommendations was evaluated in 12 studies (52.2%). Most studies reported acceptance rates exceeding 90%, including rates of 94.4%, 96.5%, and over 98% in several evaluations of pharmacist-led medication review services ( Tan et al., 2021 ; Zerbit et al., 2022 ; de Grégori et al., 2020 ). However, variation in uptake was observed. One study reported a notably lower acceptance rate of 40% for pharmacist recommendations related to antifungal prophylaxis optimization which was attributed due to the lack of standardized communication of recommendations ( Reslan et al., 2020 ), highlighting heterogeneity in implementation across settings.

Laboratory ordering and TDM processes were reported in 7 studies (30.4%). Pharmacists contributed to medication safety by recommending laboratory monitoring during therapy titration or treatment initiation, including laboratory monitoring in 33% and 35.3% of cases in two studies evaluating targeted therapies ( de Boer et al., 2025 ; Lam and Cheung, 2016 ). Implementation of a TDM protocol also increased empiric dose adjustments from three patients before protocol implementation to 14 after implementation ( p = 0.002) ( Gawedzki and Collins, 2021 ). In another study, the introduction of a TDM protocol increased the number of patients receiving monitoring from none to 14 ( Chen et al., 2020 ).

Adherence to treatment guidelines or institutional protocols was evaluated in 5 studies (21.7%). Pharmacist-led interventions were associated with improvements in several prophylaxis and supportive care practices. For example, adherence to antifungal prophylaxis guidelines increased from 31% to 54% following pharmacist intervention ( p = 0.0344) ( Reslan et al., 2020 ). Another study reported improvements in adherence to multiple clinical guidelines, including bisphosphonate therapy (96% vs. 68%, p < 0.001), influenza vaccination (76% vs. 24%, p < 0.001), antiviral prophylaxis (100% vs. 58%, p < 0.001), and venous thromboembolism prophylaxis during immunomodulatory therapy (100% vs. 83%, p = 0.0035) ( Sweiss et al., 2018 ).

Documentation practices, transitions of care, and multidisciplinary coordination were reported in 12 studies (52.2%). Pharmacist involvement contributed to improved communication across care teams, coordination of specialty medication access, and structured discharge planning. Several studies described pharmacist participation in multidisciplinary teams or transplant care coordination processes ( Virani et al., 2020 ; Ghasoub et al., 2024 ; Zanetti et al., 2023 ). Improvements in documentation and insurance communication were also reported, with one study demonstrating improvements from 0% baseline communication of insurance benefit investigations to 100% documentation for antifungal and oral chemotherapy prescriptions following pharmacist involvement ( Wind et al., 2021 ).

Process-related outcomes demonstrated that pharmacist integration improved medication safety processes, monitoring practices, and care coordination. However, variability in intervention uptake and implementation across studies indicates that the effectiveness of pharmacist-led services may depend on institutional workflows, multidisciplinary collaboration, and local practice environments. Table 5 summarizes the process-related outcomes reported across included studies.

Economic outcomes

Economic and resource-related outcomes were reported in 8 studies (24.2%). Cost savings or cost avoidance were reported in 7 studies (87.5%). Several studies quantified substantial economic benefits associated with pharmacist-led interventions. For example, one study estimated a total value of $189,441 for pharmacist interventions during a 39-day study period, corresponding to a projected annual value of $757,764 ( Virani et al., 2020 ). Similarly, another study reported more than $1 million in total drug cost avoidance through pharmacist-led therapy optimization and treatment discontinuation strategies ( Nguyen, 2023 ).

Cost-benefit or return-on-investment analyses were reported in 4 studies (50%) and generally demonstrated favorable economic returns. Reported cost-benefit ratios ranged from €3.7 per €1 invested to €7.07 per €1 invested in pharmacist-led services ( Zerbit et al., 2022 ; de Grégori et al., 2020 ). In another study, implementation of a ward-based clinical pharmacist increased pharmacist interventions and was associated with a marked improvement in benefit-cost ratio, from 0.77 to 3.19, alongside increased medication cost savings and avoidance ( Chen et al., 2020 ).

Medication-related cost reductions were reported in 5 studies (62.5%). Pharmacist involvement contributed to reduced medication expenditures through therapy optimization, dose adjustments, intravenous-to-oral switches, and facilitation of patient access to financial assistance programs. For example, one study reported savings of $197,158 through pharmacist-facilitated access to manufacturer assistance programs for high-cost therapies ( Knight et al., 2022 ), while other studies described reductions in drug expenditures through treatment discontinuation or regimen optimization ( Virani et al., 2020 ; Nguyen, 2023 ; de Grégori et al., 2020 ; Chen et al., 2020 ).

The financial impact of AEs prevention was reported in 3 studies (37.5%). Prevention or reduction of ADEs contributed substantially to avoided healthcare costs in several analyses. For example, one study identified ADE prevention as a major contributor to avoided costs ( de Grégori et al., 2020 ), while another reported increases in prevented ADEs from 58 to 230 following pharmacist integration ( Chen et al., 2020 ).

Resource utilization outcomes were reported less frequently. Length of hospital stay was evaluated in one study (12.5%), which reported a significant reduction from 19.27 to 16.69 days following integration of a ward-based clinical pharmacist ( p < 0.00001) ( Chen et al., 2020 ). Avoided hospitalizations or readmissions was reported in one study (12.5%). The study observed fewer rehospitalizations in the pharmacist-supported group, although the difference did not reach statistical significance ( p = 0.217) ( Devaux et al., 2022 ).

Formal cost-effectiveness analysis was reported in one study (12.5%), which estimated an incremental cost-effectiveness ratio of $96.03 per percentage increase in medication adherence ( Mauro et al., 2019 ). These findings show that while several studies demonstrated substantial cost savings and favorable economic returns associated with pharmacist interventions, economic evaluations were heterogeneous and often limited to institutional or service-level perspectives. Only a small proportion of studies conducted formal economic analyses, and few incorporated comprehensive health economic frameworks such as cost-effectiveness modeling or sensitivity analyses.

Table 6 summarizes the economic outcomes reported across included studies.

Table 7 summarizes all included studies across the three outcome domains (clinical, process-related, and economic), detailing the pharmacist roles, outcomes reported, and key findings of each study.

Discussion

Summary of main findings

This systematic review synthesized evidence from 33 studies evaluating pharmacist-led interventions in hematology-oncology care across clinical, process-related, and economic domains. Overall, pharmacist involvement was most consistently associated with improvements in medication management processes and care coordination, while effects on clinical outcomes were more heterogeneous and economic outcomes were less frequently evaluated. These findings align with previous systematic reviews in oncology that highlight the contribution of pharmacists to medication safety and adherence support ( Colombo et al., 2017 ; Xiang et al., 2025 ; Fentie et al., 2025 ). However, considerable heterogeneity in study design, intervention models, and outcome definitions limited direct comparisons across studies and contributed to variability in reported effects.

AEs and treatment-related toxicities were among the most frequently evaluated clinical outcomes. Pharmacists commonly contributed through activities such as medication reconciliation, identification of DDIs, TDM, and proactive toxicity management. These interventions enabled earlier detection of ADRs and medication-related problems, allowing treatment adjustments before clinically significant complications occurred ( Devaux et al., 2022 ; Gawedzki and Collins, 2021 ). In some studies, pharmacist involvement was associated with reductions in severe toxicities or improved monitoring practices, although many investigations focused primarily on the identification and management of medication-related problems rather than comparative reductions in AEs ( Tan et al., 2021 ; Farias et al., 2016 ; Albayrak and Özbalci, 2024 ). As a result, while the available evidence supports a role for pharmacists in improving medication safety, the strength of this evidence varies depending on study design and outcome measurement.

Medication adherence was another commonly evaluated outcome, particularly in studies involving long-term oral therapies. Several studies reported improvements in adherence following pharmacist-led interventions, particularly when interventions incorporated patient education, ongoing monitoring, and follow-up support ( Tan et al., 2021 ; Zerbit et al., 2020 ; Mauro et al., 2019 ; Moulin et al., 2017 ; Santoleri et al., 2019 ; Lam and Cheung, 2016 ; Opsomer et al., 2016 ; Sweiss et al., 2018 ; Sweiss et al., 2020 ). In many studies, adherence rates increased from approximately 40%–80% under usual care to 70%–100% following intervention ( Zanetti et al., 2023 ; Mauro et al., 2019 ; Santoleri et al., 2019 ; Lam and Cheung, 2016 ; Muluneh et al., 2018 ). Pharmacists frequently provided individualized counseling on medication administration, adverse effect management, and treatment expectations, which may improve patient understanding and engagement with therapy. In addition, structured follow-up mechanisms such as clinic visits, telephone monitoring, or medication refill tracking created opportunities to identify adherence barriers and intervene early. However, adherence measures varied widely across studies and often relied on indirect metrics such as medication possession ratios or self-reported adherence, limiting comparability. Moreover, adherence remains a surrogate outcome, and the extent to which these improvements translate into sustained clinical benefit remains uncertain.

Adherence challenges are particularly relevant in hematological malignancies requiring prolonged oral therapy and frequent monitoring, including chronic myeloid leukemia, chronic lymphocytic leukemia, and MM ( Stumpf and Al-Sawaf, 2024 ; Tam, 2021 ; Bonello et al., 2019 ). In these settings, pharmacist involvement may help mitigate treatment complexity by improving medication education, supporting regimen management, and reducing polypharmacy, as demonstrated by reductions in medication burden in collaborative clinic models ( Sweiss et al., 2020 ). However, the durability of these effects and their impact on long-term clinical outcomes remain insufficiently studied.

Clinical outcomes beyond adherence and toxicity demonstrated mixed findings. Some studies reported improvements in disease response, survival outcomes, or patient-reported quality of life following pharmacist-led interventions, whereas others did not observe statistically significant differences between intervention and comparator groups ( Moulin et al., 2017 ; Knight et al., 2022 ; Devaux et al., 2022 ; Muluneh et al., 2018 ). These inconsistencies likely reflect differences in patient populations, treatment regimens, and intervention intensity, as well as methodological limitations. Potential associations may also be confounded by disease severity, treatment selection, and healthcare system factors.

Evidence regarding treatment interruptions, pharmacokinetic optimization, and hospitalization outcomes was similarly limited and inconsistent. Pharmacist involvement facilitated activities such as dose titration, genomic-guided dosing, and TDM in some studies, but measurable improvements in pharmacokinetic endpoints or reductions in hospitalization were not consistently observed ( Ali et al., 2021 ; de Boer et al., 2025 ; Gawedzki and Collins, 2021 ). As a result, the limited number of studies restricts the strength of conclusions that can be drawn.

In contrast to the variability observed in clinical outcomes, process-related outcomes demonstrated more consistent improvements across studies. Pharmacists frequently identified and resolved DRPs, detected DDIs, and implemented clinical interventions aimed at optimizing therapy. Several studies reported large numbers of pharmacist interventions, ranging from hundreds to thousands of interventions within relatively short study periods ( Zerbit et al., 2022 ; Ali et al., 2021 ; Nguyen, 2023 ; de Grégori et al., 2020 ). DRPs were commonly identified and frequently resolved following pharmacist intervention, with reported resolution rates exceeding 75% in some studies ( Tan et al., 2021 ; Albayrak and Özbalci, 2024 ). These interventions often occurred within multidisciplinary care models where pharmacists served as medication experts, supporting prescribing decisions and enhancing communication between healthcare providers. Acceptance of pharmacist recommendations by prescribers was generally high, often exceeding 90% ( Tan et al., 2021 ; Zerbit et al., 2022 ; Albayrak and Özbalci, 2024 ; Ghasoub et al., 2024 ; Mansour et al., 2024 ; de Grégori et al., 2020 ; Prot-Labarthe et al., 2008 ). However, this observation was not uniform across studies. One study reported a substantially lower uptake rate of 40% for pharmacist recommendations ( Reslan et al., 2020 ), highlighting variability in interprofessional integration and implementation of pharmacist interventions across healthcare settings.

From a process perspective, pharmacist involvement frequently reshaped clinical workflows within hematology-oncology care teams. Pharmacists commonly participated in multidisciplinary rounds, coordinated transitions of care, and implemented structured monitoring practices such as TDM protocols and laboratory surveillance ( Farias et al., 2016 ; Larbre et al., 2025 ; Reslan et al., 2020 ; Wind et al., 2021 ; Gawedzki and Collins, 2021 ; Prot-Labarthe et al., 2008 ; Chen et al., 2020 ; Chen et al., 2020 ; Sweiss et al., 2020 ). In several studies, pharmacist-led initiatives introduced systematic approaches to guideline implementation, prophylaxis protocols, and supportive care management ( Reslan et al., 2020 ; Sweiss et al., 2020 ). By embedding these activities into routine clinical practice, pharmacist involvement helped standardize medication management processes in complex oncology settings. However, many interventions were implemented in tertiary or academic centers with established infrastructure, which may limit generalizability to non-tertiary or resource-limited environments. In addition, several programs were implemented as pilot or early-stage service models within highly motivated clinical teams, raising the possibility of implementation bias related to early adopters ( Mauro et al., 2019 ; Mansour et al., 2024 ).

Economic outcomes were evaluated less frequently and demonstrated considerable methodological heterogeneity. Several studies reported cost savings or cost avoidance associated with pharmacist interventions, often attributed to prevention of ADEs, optimization of chemotherapy regimens, and improved medication access through financial assistance programs ( Virani et al., 2020 ; Nguyen, 2023 ; de Grégori et al., 2020 ). Pharmacists also contributed to cost reductions through therapy optimization, intravenous-to-oral medication switches, and avoidance of unnecessary medications.

In addition to direct financial metrics, some studies reported improvements in healthcare resource utilization, such as reductions in hospital length of stay or rehospitalizations. These measures often reflect improved clinical management, including better toxicity control, early identification of adverse events, and optimized supportive care. Consequently, these clinical improvements may translate into downstream economic benefits by reducing hospitalization costs and overall healthcare utilization.

Some analyses suggested favorable economic returns for pharmacist services; however, most economic evaluations relied on short-term institutional analyses or modeled cost avoidance estimates rather than comprehensive cost-effectiveness frameworks ( Zerbit et al., 2022 ; Virani et al., 2020 ; Nguyen, 2023 ; de Grégori et al., 2020 ; Prot-Labarthe et al., 2008 ; Chen et al., 2020 ). The lack of standardized economic evaluation methods and long-term follow-up limits the strength of conclusions regarding the economic value of pharmacist-led interventions.

When considered collectively, the findings across clinical, process, and economic domains suggest that pharmacist-led interventions primarily influence medication management processes, which in turn may contribute to improvements in medication safety, adherence, and healthcare resource utilization. Pharmacists frequently implemented structured medication management strategies addressing multiple aspects of treatment delivery, including medication review, toxicity monitoring, dose adjustment, TDM, and patient education. These findings suggest that pharmacist interventions operate through a multifaceted approach combining medication optimization, patient education, and systematic monitoring, which together improve treatment safety and continuity of care.

Based on the available data, the strength of evidence varies across outcome categories. Process-related outcomes and medication safety measures are supported by the most consistent findings across studies, reflecting the direct role pharmacists play in medication management. Evidence for improvements in medication adherence is moderately supportive but limited by variability in adherence measurement methods and study design. In contrast, evidence linking pharmacist involvement to survival outcomes, disease response, or economic benefit remains exploratory due to the small number of studies assessing these outcomes and the predominance of observational designs.

These findings are summarized in Table 8 , which categorizes the strength of evidence across outcome domains.

Implications for practice

Despite the methodological limitations identified across the included studies, the overall body of evidence supports the integration of pharmacists into hematology-oncology care teams, particularly in roles focused on medication safety, adherence support, toxicity monitoring, and care coordination. Hematological malignancies often require complex treatment regimens involving targeted therapies, immunomodulatory agents, and supportive care medications that require ongoing monitoring and management. In this context, pharmacist-led interventions may help address common challenges such as polypharmacy, DDIs, toxicity management, and adherence to long-term oral therapies.

From a policy and health-system perspective, broader implementation of clinical pharmacy services should be supported by standardized outcome measures, integration into multidisciplinary care models, and robust economic evaluations that account for local resource constraints and system priorities ( Salman et al., 2025 ). These findings are consistent with recommendations from professional bodies such as the American Society of Health-System Pharmacists, the European Society for Medical Oncology, and the National Comprehensive Cancer Network, which emphasize the role of oncology pharmacists in optimizing medication safety, quality, and value ( Hernandez et al., 2025 ; Ranchon et al., 2025 ; Schwartz et al., 2010 ).

Future research should prioritize prospective, well-controlled study designs, including pragmatic or cluster-randomized trials, to better define the causal impact of pharmacist-led interventions in hematology care. The adoption of standardized outcome sets incorporating validated adherence measures, medication safety indicators, PROs, and resource utilization, with clearly defined assessment time points, would improve comparability and facilitate evidence synthesis ( Chung et al., 2019 ; Salman et al., 2025 ). Further evaluation of scalability, sustainability, and long-term economic impact, particularly in non-tertiary and resource-limited settings, is needed to strengthen the evidence base for integrating pharmacists into hematology services.

Strengths and limitations

A key strength of this review is the detailed characterization of pharmacist roles, intervention components, and outcome domains, which provides a structured overview of pharmacist involvement in hematology-oncology care. The inclusion of both prospective and retrospective studies allowed for a broad synthesis that captures evidence from controlled evaluations as well as real-world practice settings.

Several methodological approaches were applied to support robust interpretation of the available evidence. Critical appraisal was conducted using the JBI framework with domain-level assessment, allowing the methodological quality of individual studies to be considered when interpreting findings. Conclusions were therefore framed in accordance with study design and methodological quality, with clear differentiation between exploratory and confirmatory studies. In addition, a structured narrative synthesis was used to integrate findings across heterogeneous study designs while maintaining transparency regarding study characteristics and reported outcomes.

Despite these strengths, several limitations may affect the certainty and generalizability of the findings. Randomized evidence was limited, and most included studies utilized observational or quasi-experimental designs. Blinded outcome assessment was infrequently reported, which may increase susceptibility to detection bias for some outcomes. However, the review addressed this by carefully contextualizing reported associations and avoiding causal interpretations where methodological limitations were present.

Considerable heterogeneity was observed in intervention design, outcome definitions, and follow-up duration. Rather than attempting inappropriate quantitative pooling, the narrative synthesis grouped findings by outcome domain and intervention characteristics. This approach allowed the review to capture the multifaceted nature of pharmacist-led interventions while preserving transparency in the interpretation of results.

Reporting of pharmacist training, intervention fidelity, and resource utilization was variable across studies, which may affect assessment of reproducibility and scalability. Similarly, economic evaluations frequently relied on short-term cost avoidance estimates rather than comprehensive health economic analyses. These factors were explicitly considered during interpretation, and economic findings were presented cautiously without making definitive claims regarding long-term cost-effectiveness.

Data availability influenced synthesis in some instances. A small number of studies reported limited outcome detail or combined hematological and solid tumor populations, precluding hematology-specific interpretation. Where outcome reporting was incomplete or populations were combined, findings were described cautiously, and attempts were made to obtain disaggregated data from authors.

Finally, publication bias cannot be excluded. Conference abstracts were excluded to ensure inclusion of peer-reviewed full texts with sufficient methodological detail, but this may have increased the risk of publication bias in a rapidly evolving field. The evidence base was also dominated by studies conducted in high-income healthcare systems, most of which reported favorable findings. This imbalance may overestimate intervention effectiveness and limits applicability to primary care settings, resource-limited settings, and lower- and middle-income countries.

Despite these limitations, a substantial number of studies consistently demonstrated beneficial effects of pharmacist-led interventions across several outcome domains. The consistency of these findings across diverse study designs and practice settings strengthens confidence in the overall conclusions, while highlighting the need for further high-quality controlled studies to strengthen causal inference and evaluate long-term clinical and economic outcomes.

Conclusion

This systematic review demonstrates that pharmacist-led interventions play an important role in optimizing medication management in hematology-oncology care. Across the included studies, pharmacist involvement most consistently improved medication-related processes, including identification and resolution of DRPs, management of drug interactions, adherence support, and coordination of care within multidisciplinary teams. Overall, the available evidence supports the integration of pharmacists into hematology-oncology care teams as a strategy to enhance medication safety and treatment management for patients receiving complex therapies. However, more prospective studies using standardized clinical, patient-reported, and economic outcome measures are needed to more clearly define the long-term clinical and health system impact of pharmacist-led interventions in this setting.

Edited by: Junan Li , The Ohio State University, United States

Reviewed by: Zaiwei Song , Peking University Third Hospital, China

Chun-Nan Kuo , Taipei Medical University, Taiwan

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author.

Author contributions

AM: Data curation, Writing – original draft, Conceptualization, Methodology, Formal Analysis, Writing – review and editing. BS: Formal Analysis, Validation, Methodology, Supervision, Investigation, Writing – review and editing, Writing – original draft. RA: Formal Analysis, Validation, Methodology, Writing – review and editing, Writing – original draft. KA-F: Writing – review and editing, Supervision, Formal Analysis, Writing – original draft. MY: Writing – review and editing, Writing – original draft, Supervision, Formal Analysis.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author MY declared that they were an editorial board member of Frontiers at the time of submission. This had no impact on the peer review process and the final decision.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphar.2026.1779201/full#supplementary-material

References

Albayrak A. Özbalci D. ( 2024 ). Determination of drug-related problems in the hematology service: a prospective interventional study . BMC CANCER 24 , 552 . 10.1186/s12885-024-12291-w 38698336 PMC11067252

Ali K. Al-Quteimat O. Naseem R. Malhi S. Wajdi M. Jahan N. ( 2021 ). Incorporating a clinical oncology pharmacist into an ambulatory care pharmacy in pediatric hematology-oncology and transplant clinic: assessment and significance . J. Oncol. Pharm. Pract. 27 , 815 – 820 . 10.1177/1078155220934167 32633660

Banez M. T. Atienza S. Butts A. Derba M. Dicke K. Haverstick K. ( 2024 ). Oncology stewardship practice in the United States: a hematology/oncology pharmacy association national survey . J. Oncol. Pharm. Pract. 31 , 10781552241265280 – 10781552241265527 . 10.1177/10781552241265280 39091073

Bonello F. Cetani G. Bertamini L. Gay F. Larocca A. ( 2019 ). Moving toward continuous therapy in multiple myeloma . Clin. Hematol. Int. 1 , 189 – 200 . 10.2991/chi.d.191101.001 34595430 PMC8432368

Campbell C. ( 2012 ). Outcomes of chronic myelogenous leukemia and adherence to imatinib therapy (CML-AIT) study. Abstract# 60; platform category A2 . Monterey Bay, California: 32nd Annual Meeting of the Western State Residency Conference .

Chen P.-Z. Wu C.-C. Huang C.-F. ( 2020 ). Clinical and economic impact of clinical pharmacist intervention in a hematology unit . J. Oncol. Pharm. Pract. 26 , 866 – 872 . 10.1177/1078155219875806 31566112

Chung C. Kim S. Bubalo J. ( 2019 ). Instilling value, quality, and safety through hematology and oncology stewardship . Am. J. Health Syst. Pharm. 76 , 617 – 621 . 10.1093/ajhp/zxz036 30915457

Colombo L. R. P. Aguiar P. M. Lima T. M. Storpirtis S. ( 2017 ). The effects of pharmacist interventions on adult outpatients with cancer: a systematic review . J. Clin. Pharm. Ther. 42 , 414 – 424 . 10.1111/jcpt.12562 28556392

de Boer A. McCaw C. Ackman M. Leslie T. Peters A. Koshman S. ( 2025 ). Evaluating the impact of a pharmacist-led venetoclax ramp-up clinic for chronic lymphocytic leukemia patients: a retrospective chart review . J. Oncol. Pharm. Pract. , 10781552251324522 . 10.1177/10781552251324522 40116626

de Grégori J. Pistre P. Boutet M. Porcher L. Devaux M. Pernot C. ( 2020 ). Clinical and economic impact of pharmacist interventions in an ambulatory hematology–oncology department . J. Oncol. Pharm. Pract. 26 , 1172 – 1179 . 10.1177/1078155220915763 32299314

Devaux M. Boulin M. Mounier M. Caillot D. Ahwij N. Herbin A. ( 2022 ). Clinical and economic impact of a multidisciplinary Follow-Up program in lymphoma patients . CANCERS 14 , 2532 . 10.3390/cancers14102532 35626136 PMC9139274

Farias T. F. Aguiar K. D. Rotta I. Belletti K. M. Carlotto J. ( 2016 ). Implementing a clinical pharmacy service in hematology . Einstein Sao Paulo Braz 14 , 384 – 390 . 10.1590/S1679-45082016AO3667 27759828 PMC5234751

Fentie A. M. Huluka S. A. Gebremariam G. T. Gebretekle G. B. Abebe E. Fenta T. G. ( 2025 ). Impact of pharmacist-led interventions on medication-related problems among patients treated for cancer: a systematic review and meta-analysis of randomized control trials . Res. Soc. Adm. Pharm. 20 , 487 – 497 . 10.1016/j.sapharm.2024.02.006 38368123

Gawedzki P. Collins J. ( 2021 ). Impact of the implementation of a pharmacist-driven immunosuppression drug monitoring protocol for hematopoietic stem cell transplant recipients . J. Oncol. Pharm. Pract. 27 , 1907 – 1913 . 10.1177/1078155220975088 33250016

Ghasoub R. Elazzazy S. Benkhadra M. Kassem N. Cherif H. Gaziev J. ( 2024 ). Establishment of a clinical pharmacist-led multiple myeloma clinic with collaborative prescribing model at the national center for cancer care and research in Qatar . J. Am. Pharm. Assoc. 64 , 102141 . 10.1016/j.japh.2024.102141 38844021

Gonçalves T. S. Fontes L. F. Nascimento F. B. G. do Nascimento M. M. G. de Lima Santos P. C. J. ( 2025 ). Improving pediatric oncology knowledge through pharmaceutical health education . J. Cancer Educ. 40 , 854 – 858 . 10.1007/s13187-025-02584-4 39982682

Haddaway N. R. Page M. J. Pritchard C. C. McGuinness L. A. ( 2022 ). PRISMA2020: an R package and shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimised digital transparency and open synthesis campbell systematic reviews . Campbell Syst. Rev. 18 , e1230 . 10.1002/cl2.1230 36911350 PMC8958186

Hernandez K. Doh J. Lustberg M. Chan A. ( 2025 ). Strengthening supportive care: leveraging the expanding role of oncology pharmacists . JCO Oncol. Adv. 2 , e2500180 . 10.1200/OA-25-00180

Hilton M. ( 2024 ). JBI critical appraisal checklist for systematic reviews and research syntheses . J. Can. Health Libr. Assoc. 45 , 180 – 183 . 10.29173/jchla29801

Hou J.-Z. Ye J. C. Pu J. J. Liu H. Ding W. Zheng H. ( 2021 ). Novel agents and regimens for hematological malignancies: recent updates from 2020 ASH annual meeting . J. Hematol. OncolJ Hematol. Oncol. 14 , 66 . 10.1186/s13045-021-01077-3 33879198 PMC8059303

Howell D. A. McCaughan D. Smith A. G. Patmore R. Roman E. ( 2022 ). Incurable but treatable: understanding, uncertainty and impact in chronic blood cancers—A qualitative study from the UK’s haematological malignancy research network . PLOS ONE 17 , e0263672 . 10.1371/journal.pone.0263672 35143569 PMC8830712

Joanna Briggs Institute ( 2017a ). Joanna briggs institute 2017 critical appraisal checklist for case control studies. Case control stud 2017 . Available online at: https://jbi.global/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Case_Control_Studies2017_0.pdf (Accessed September 27, 2025).

Joanna Briggs Institute ( 2017b ). Joanna briggs institute 2017 critical appraisal checklist for cohort studies . Available online at: https://jbi.global/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Cohort_Studies2017_0.pdf (Accessed September 27, 2025).

Joanna Briggs Institute ( 2017c ). Joanna briggs institute 2017 critical appraisal checklist for analytical cross sectional studies . Available online at: https://jbi.global/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Analytical_Cross_Sectional_Studies2017_0.pdf (Accessed September 27, 2025).

Joanna Briggs Institute ( 2017d ). Joanna briggs institute 2017 critical appraisal checklist for economic evaluations 2017 . Available online at: https://jbi.global/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Economic_Evaluations2017_0.pdf (Accessed September 27, 2025).

Joanna Briggs Institute ( 2020a ). Joanna briggs institute 2020 critical appraisal checklist for randomized controlled trials . Available online at: https://jbi.global/sites/default/files/2020-08/Checklist_for_RCTs.pdf (Accessed September 27, 2025) .

Joanna Briggs Institute ( 2020b ). Joanna briggs institute 2020 critical appraisal checklist for quasi-experimental studies (non-randomized experimental studies) . Available online at: https://jbi.global/sites/default/files/2020-08/Checklist_for_Quasi-Experimental_Appraisal_Tool.pdf (Accessed September 27, 2025) .

Knight T. G. Aguiar M. Robinson M. Morse A. Chen T. Bose R. ( 2022 ). Financial toxicity intervention improves outcomes in patients with hematologic malignancy . JCO Oncol. Pract. 18 , e1494 – e1504 . 10.1200/OP.22.00056 35709421

Lam M. S. H. Cheung N. ( 2016 ). Impact of oncology pharmacist-managed oral anticancer therapy in patients with chronic myelogenous leukemia . J. Oncol. Pharm. Pract. 22 , 741 – 748 . 10.1177/1078155215608523 26419691

Larbre V. Ranchon F. Maucort-Boulch D. Coz E. Herledan C. Caffin A.-G. ( 2025 ). Oncoral Follow-Up for outpatients treated with oral anticancer drugs assessed by relative dose intensity . Pharmaceuticals 18 , 565 . 10.3390/ph18040565 40284000 PMC12030289

Lucena M. Bondarenka C. Luehrs-Hayes G. Perez A. ( 2018 ). Evaluation of a medication intensity screening tool used in malignant hematology and bone marrow transplant services to identify patients at risk for medication-related problems . J. Oncol. Pharm. Pract. 24 , 243 – 252 . 10.1177/1078155217690923 29284343

Muluneh B. Schneider M. Faso A. Amerine L. Daniels R. Crisp B. ( 2018 ). Improved adherence rates and clinical outcomes of an integrated, closed-loop, pharmacist-led oral chemotherapy management program . J. Oncol. Pract. 14 , e324 – e334 . 10.1200/JOP.17.00039 29799768

Mansour S. Mekaouche F. Z. N. Rouabah H. Brahim S. Boudia F. Yafour N. ( 2024 ). Comprehensive medication management (CMM): application of a new pharmaceutical practice in onco-hematology . Ann. Pharm. Fr. 82 , 873 – 885 . 10.1016/j.pharma.2024.05.001 38729518

Markouli M. Ullah F. Unlu S. Omar N. Lopetegui-Lia N. Duco M. ( 2023 ). Toxicity profile of chimeric antigen receptor T-Cell and bispecific antibody therapies in multiple myeloma: pathogenesis, prevention and management . Curr. Oncol. 30 , 6330 – 6352 . 10.3390/curroncol30070467 37504327 PMC10378049

Mauro J. Mathews K. B. Sredzinski E. S. ( 2019 ). Effect of a smart pill bottle and pharmacist intervention on medication adherence in patients with multiple myeloma new to lenalidomide therapy . J. Manag. Care Spec. Pharm. 25 , 1244 – 1254 . 10.18553/jmcp.2019.25.11.1244 31663462 PMC10398191

McMenamin A. Turi E. Schlak A. Poghosyan L. ( 2023 ). A systematic review of outcomes related to nurse practitioner-delivered primary care for multiple chronic conditions . Med. Care Res. Rev. MCRR 80 , 563 – 581 . 10.1177/10775587231186720 37438917 PMC10784406

Moulin S. M. M. Eutrópio F. J. Souza J. O. Busato F. O. Olivieri D. N. Tadokoro C. E. ( 2017 ). The role of clinical pharmacists in treatment adherence: fast impact in suppression of chronic myeloid leukemia development and symptoms . Support Care Cancer 25 , 951 – 955 . 10.1007/s00520-016-3486-6 27866336

Munn Z. Barker T. H. Moola S. Tufanaru C. Stern C. McArthur A. ( 2019 ). Methodological quality of case series studies: an introduction to the JBI critical appraisal tool . JBI Database Syst. Rev. Implement Rep. 18 ( 10 ), 2127 – 2133 . 10.11124/JBISRIR-D-19-00099 33038125

Nguyen A. L. ( 2023 ). Impact of oral chemotherapy pharmacists on cost avoidance of oral oncolytics in an integrated health system . J. Oncol. Pharm. Pract. 29 , 1369 – 1373 . 10.1177/10781552221122034 36002947

Nucci M. Anaissie E. J. ( 2017 ). Prevention of infections in patients with hematological malignancies . Neoplast. Dis. Blood , 1047 – 1062 . 10.1007/978-3-319-64263-5_49

Ochs M. A. Marini B. L. Perissinotti A. J. Foucar C. E. Pettit K. Burke P. ( 2022 ). Oncology stewardship in acute myeloid leukemia . Ann. Hematol. 101 , 1627 – 1644 . 10.1007/s00277-022-04872-1 35618780

Opsomer M.-A. Anota A. Noblot-Rossignol M. Bonnetain F. Pernot C. Chretien M.-L. ( 2016 ). Impact of pharmaceutical intervention on quality of life and coping strategies in patients with haematological malignancies . Ann. Pharm. Fr. 74 , 439 – 447 . 10.1016/j.pharma.2016.03.007 27162122

Page M. J. McKenzie J. E. Bossuyt P. M. Boutron I. Hoffmann T. C. Mulrow C. D. ( 2021 ). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews . BMJ 372 , n71 . 10.1136/bmj.n71 33782057 PMC8005924

Périchou J. Ranchon F. Herledan C. Huot L. Larbre V. Carpentier I. ( 2020 ). Immunomodulatory drugs in multiple myeloma: impact of the SCARMET (self CARe and MEdication toxicity) educational intervention on outpatients’ knowledge to manage adverse effects . PloS One 15 , e0243309 . 10.1371/journal.pone.0243309 33275634 PMC7717911

Prot-Labarthe S. Therrien R. Demanche C. Larocque D. Bussières J.-F. ( 2008 ). Pharmaceutical care in an inpatient pediatric hematopoietic stem cell transplant service . J. Oncol. Pharm. Pract. 14 , 147 – 152 . 10.1177/1078155208093929 18719069

Ranchon F. Slimano F. Borget I. Boulin M. Bardin C. Coliat P. ( 2025 ). Oncology pharmacy practice: key insights, challenges, and perspectives – a position paper from the French society for oncology pharmacy (SFPO) . Ann. Pharm. Fr. 83 , 1040 – 1052 . 10.1016/j.pharma.2025.07.005 40651529

Reslan Z. Lindsay J. Kerridge I. Gellatly R. ( 2020 ). Pharmacist review of high-risk haematology outpatients to improve appropriateness of antifungal prophylaxis . Int. J. Clin. Pharm. 42 , 1412 – 1418 . 10.1007/s11096-020-01090-5 33009604

Salman B. Mohamed A. Al-Riyami I. Hamad A. Al-Khabori M. ( 2025 ). Oncology stewardship: a narrative review of principles and practices . J. Oncol. Pharm. Pract. , 10781552251372492 . 10.1177/10781552251372492 40879419

Santoleri F. Lasala R. Logreco A. Ranucci E. Costantini A. ( 2019 ). Using a treatment diary to improve the medication adherence in patients with chronic myeloid leukaemia . J. Oncol. Pharm. Pract. 25 , 1035 – 1041 . 10.1177/1078155218759184 29460706

Schwartz R. N. Eng K. J. Frieze D. A. Gosselin T. K. Griffith N. Seung A. H. ( 2010 ). NCCN task force report: specialty pharmacy . J. Natl. Compr. Cancer Netw. JNCCN 8 ( Suppl. 4 ), S1 – S12 . 10.6004/jnccn.2010.0127 20705807

Siddiqui A. Shrestha S. Ahmed A. Akhlaq Bhutta O. ( 2023 ). Oncology stewardship: role of the pharmacists for contribution in low and middle-income countries . J. Oncol. Pharm. Pract. 29 , 956 – 957 . 10.1177/10781552231154465 36734132 PMC10273846

Sochacka-Ćwikła A. Mączyński M. Regiec A. ( 2021 ). FDA-approved drugs for hematological malignancies—the last decade review . Cancers 14 , 87 . 10.3390/cancers14010087 35008250 PMC8750348

Stumpf J. Al-Sawaf O. ( 2024 ). Chronic lymphocytic leukemia: time-limited therapy in the first-line setting and role of minimal residual disease . Curr. Oncol. Rep. 26 , 136 – 146 . 10.1007/s11912-023-01482-6 38175465 PMC10891251

Sweiss K. Wirth S. M. Sharp L. Park I. Sweiss H. Rondelli D. ( 2018 ). Collaborative physician-Pharmacist–Managed multiple myeloma clinic improves guideline adherence and prevents treatment delays . J. Oncol. Pract. 14 , e674 – e682 . 10.1200/JOP.18.00085 30423263

Sweiss K. Calip G. S. Wirth S. Rondelli D. Patel P. ( 2020 ). Polypharmacy and potentially inappropriate medication use is highly prevalent in multiple myeloma patients and is improved by a collaborative physician–pharmacist clinic . J. Oncol. Pharm. Pract. 26 , 536 – 542 . 10.1177/1078155219851550 31189419

Tam C. S. ( 2021 ). Upfront therapy: the case for continuous treatment . Hematol. Am. Soc. Hematol. Educ. Program 2021 , 55 – 58 . 10.1182/hematology.2021000232 34889433 PMC8791150

Tan B. K. Chua S. S. Chen L.-C. Chang K. M. Balashanker S. Bee P. C. ( 2021 ). Acceptability of pharmacist-led interventions to resolve drug-related problems in patients with chronic myeloid leukaemia . J. Oncol. Pharm. Pract. Off. Publ. Int. Soc. Oncol. Pharm. Pract. 27 , 1644 – 1656 . 10.1177/1078155220964539 33040675

Tang L. Huang Z. Mei H. Hu Y. ( 2023 ). Immunotherapy in hematologic malignancies: achievements, challenges and future prospects . Signal Transduct. Target Ther. 8 , 306 . 10.1038/s41392-023-01521-5 37591844 PMC10435569

Virani A. Schlei Z. Gleason C. Ackermann M. Wolfe B. Major S. ( 2020 ). Impact of an oncology clinical pharmacist specialist in an outpatient multiple myeloma clinic . Clin. Lymphoma Myeloma Leuk. 20 , e543 – e546 . 10.1016/j.clml.2020.04.012 32605900

Wind L. S. Knight T. G. Auten J. J. Bates J. S. Marucci L. Creedle C. J. ( 2021 ). Evaluation and optimization of a clinical pharmacist driven transitions of care model for malignant hematology . J. Oncol. Pharm. Pract. 27 , 283 – 287 . 10.1177/1078155220916516 32290764

Wyatt H. White S. Holloway H. DeClercq J. Zuckerman A. D. Choi L. ( 2025 ). Integrated health system pharmacy role in adherence, persistence, and adverse effect management for oral chronic lymphocytic leukemia therapy . J. Manag. Care Spec. Pharm. 31 , 253 – 261 . 10.18553/jmcp.2025.31.3.253 40021460 PMC11871158

Xiang H.-W. Shen Y.-Y. Wang J.-X. Zhao Y. Yi B.-W. Zhao N. ( 2025 ). Impact of pharmacist-led interventions on oncology drug therapy outcomes: a systematic review and meta-analysis . Int. J. Pharm. Pract. 34 , riaf098 . 10.1093/ijpp/riaf098 41159575

Zanetti M. O. B. Rodrigues J. P. V. Varallo F. R. Cunha R. L. G. Simões B. P. Pereira L. R. L. ( 2023 ). Impact of the insertion of the clinical pharmacist in the allogeneic hematopoietic stem cells transplantation team . J. Oncol. Pharm. Pract. 29 , 375 – 385 . 10.1177/10781552211073797 35037789

Zerbit J. Chevret S. Bernard S. Kroemer M. Ablard C. Harel S. ( 2020 ). Improved time to treatment failure and survival in ibrutinib-treated malignancies with a pharmaceutical care program: an observational cohort study . Ann. Hematol. 99 , 1615 – 1625 . 10.1007/s00277-020-04045-y 32483668 PMC7316844

Zerbit J. Kroemer M. Fuchs B. Detroit M. Decroocq J. Vignon M. ( 2022 ). Pharmaceutical cancer care for haematology patients on oral anticancer drugs: findings from an economic, clinical and organisational analysis . Eur. J. Cancer Care (Engl) 31 , e13753 . 10.1111/ecc.13753 36273820