A Comprehensive Review of Methods to Measure Oral Oncolytic Dose Intensity Using Retrospective Data.

BACKGROUND: Understanding the real-world use of oral oncolytics is essential to assess drug effectiveness. Retrospective analyses using medical and pharmacy claims data allow observation of drug use patterns and health outcomes. However, studies of medication adherence to oral oncolytics may not be sufficient in characterizing exposure because they typically measure refill frequency, not the administered dose or dose changes. Patients who appear fully adherent by traditional measures may be receiving different doses and experiencing differing effectiveness. Relative dose intensity (RDI) is a measure that has been used for intravenous drugs to capture the amount of a particular chemotherapeutic agent administered per unit of time (dose intensity), expressed as the fraction of the amount recommended in evidence-based guidelines. Such a measure would be useful for real-world studies of comparative effectiveness to characterize patient exposure to oral oncolytics. OBJECTIVE: To identify studies that used administrative claims data to measure real-world oral oncolytic dose intensity, RDI, or similar constructs. METHODS: Two health sciences librarians conducted a literature search (PubMed, January 1, 1809-February 6, 2018) including terms in each of the following concept areas: oncology drugs, dosage, and retrospective data sources. At least 2 reviewers scanned each title and abstract of publications retrieved from PubMed. Abstracts that indicated the study reported dose or related concepts and oral oncolytics using retrospective data sources were marked for full-text review. During full-text review, papers were excluded if they did not study oral oncolytics (i.e., only described intravenous chemotherapy); if they did not report drug dosage; or if the study was not retrospective. Resulting studies were included for full-text data extraction. RESULTS: Of the 1,640 publications returned from the search, 41 were marked for full-text review. Full-text review established that 17 studies addressed a concept related to dose of oral oncolytics using retrospective data. Twenty-four studies were excluded: 11 did not measure dose; 9 did not study oral oncolytics; and 4 were not retrospective studies. Among the 17 articles marked for extraction, 5 articles reported dose intensity or RDI using medical records or electronic health record (EHR) data. CONCLUSIONS: This study reveals not only the need for a claims-based measure of dose intensity for oral oncolytics, but also provides a basis for the development of such a measure based on previous EHR-based studies. While several claims data studies have characterized oral oncolytic dosing and duration, we found that no studies combined these dimensions into a single measure such as dose intensity. Methods using EHR data may be translatable to a claims data study. Future research is needed to develop and validate such measures. DISCLOSURES: Novartis Pharmaceuticals provided funding for this study and is a manufacturer of oral onalytics, which is under study in this article. Arcona and Zacker are employees of Novartis. Slejko reports grants from PhRMA, PhRMA Foundation, and Takeda Pharmaceuticals and consulting fees from Pfizer, outside the submitted work. Stuart reports consulting fees from the University of Maryland during the study. The other authors have nothing to disclose. The preliminary findings of this study were presented in a poster at AMCP Nexus 2018, October 22-25, 2018, in Orlando, FL.

Quantification of Economic Impact of Drug Wastage in Oral Oncology Medications: Comparison of 3 Methods Using Palbociclib and Ribociclib in Advanced or Metastatic Breast Cancer.

BACKGROUND: Discarding unused drugs after dose changes or discontinuation can significantly affect pharmacy budgets. This is especially concerning for expensive oncology agents. However, few economic studies account for drug wastage, providing an inaccurate estimate of a drug's actual economic cost, cost-effectiveness, and value. OBJECTIVES: To (a) compare the economic impact of drug wastage between ribociclib and palbociclib-clinically similar oral medications for metastatic breast cancer-using 3 approaches (Markov model, pharmacy acquisition cost model, and a retrospective claims analysis) and (b) compare the modeling results with a published estimate of drug wastage for palbociclib from a claims analysis. METHODS: A Markov model and a pharmacy acquisitions cost model were developed to evaluate the economic impact of dose reductions for ribociclib and palbociclib over a 1-year time period. Data inputs were pharmacy costs (RED BOOK wholesale acquisition cost) and proportion of patients experiencing dose reductions from either ribociclib randomized clinical trials (MONALEESA-2, -3, or -7) or real-world observational data (Symphony Health retrospective claims analysis). The latter constituted the third approach for quantifying drug wastage. The economic impact of dose reductions for ribociclib and palbociclib in postmenopausal women with previously untreated HR-positive/HER2-negative advanced breast cancer was assessed. Drug wastage was defined as drug doses that could not be used by a patient following a dose reduction. The cost of drug wastage was defined as the cost associated with an unused drug resulting from a dose reduction. The predicted results from the 2 models were compared with a previously published claims analysis that estimated the effect of treatment costs and drug wastage for palbociclib based on the observed dosing patterns from the Symphony Health Solutions database. RESULTS: In the Markov model, relative to ribociclib, palbociclib users experienced drug wastage of $112,382 total, or $1,124 per treated patient, per year due to dose changes. In the pharmacy acquisition cost model, relative to ribociclib, palbociclib usage was associated with an increased cost of $7,196 per patient per year (based on a mid-cycle dose reduction) comprising dosing-based cost differences and drug wastage cost for palbociclib of $3,727. The previously published claims analysis found that palbociclib users experiencing a dose reduction had drug wastage costs of $5,471 per patient. CONCLUSIONS: In both models, dose reductions for ribociclib patients resulted in no wastage, since unused tablets could be administered in subsequent cycles, while dose reductions for palbociclib resulted in drug wastage and increased costs. The results from both models were consistent with previously published results from the claims analysis, demonstrating drug wastage costs for palbociclib. DISCLOSURES: This study received financial support from Novartis Pharmaceuticals, which has products approved for treatment of breast cancer. Tang was employed by Novartis during this study; Zacker and Dalal are employed by Novartis and own company stock. Biskupiak, Brixner, and Oderda received payment from Novartis for this study. Brixner serves as a consultant for Millcreek Outcomes Group and also declares consulting fees from Abbvie, AstraZeneca, Abbott, Becton Dickinson, and Xcenda, unrelated to this study.

The Value of Progression-Free Survival in Metastatic Breast Cancer: Results From a Survey of Patients and Providers.

Background. Value assessments and treatment decision making typically focus on clinical endpoints, especially overall survival (OS). However, OS data are not always available, and surrogate markers may also have some value to patients. This study sought to estimate preferences for progression-free survival (PFS) relative to OS in metastatic breast cancer (mBC) among a diverse set of stakeholders-patients, oncologists, and oncology nurses-and estimate the value patients and providers place on other attributes of treatment. Methods. Utilizing a combined conjoint analysis and discrete choice experiment approach, we conducted an online prospective survey of mBC patients and oncology care providers who treat mBC patients across the United States. Results. A total of 299 mBC patients, 100 oncologists, and 99 oncology nurses completed the survey. Virtually all patients preferred health state sequences with contiguous periods of PFS, compared with approximately 85% and 75% of nurses and oncologists, respectively. On average, longer OS was significantly (P < 0.01) preferred by the majority (75%) patients, but only 15% of nurses preferred longer OS, and OS did not significantly affect oncologists' preferred health state. However, in the context of a treatment decision, whether a treatment offered continuous periods of stable disease holding OS constant significantly affected nurses' treatment choices. Patients and providers alike valued reductions in adverse event risk and evidence from high-quality randomized controlled clinical trials. Conclusions. The strong preference for observed PFS suggests more research is warranted to better understand the reasons for PFS having positive value to patients. The results also suggest a range of endpoints in clinical trials may have importance to patients.

Barriers and facilitators to shared decision-making in oncology: a systematic review of the literature.

PURPOSE: Shared decision-making (SDM) is a strategy to facilitate patient-centered care and is increasingly important in oncology, where patients are faced with complicated treatment decisions that require them to weigh efficacy and safety, quality of life, and cost. Understanding the contributors to the use of SDM may provide insight to its further implementation. Therefore, the objective of the study was to examine the patient-related barriers/facilitators to SDM in oncology care. METHODS: A systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was executed. A search strategy composed of cancer, decision-making, and patient-centered terms was conducted utilizing PubMed, EBSCO MEDLINE, Scopus, CINAHL, and the Cochrane Library databases between January 2007 and November 2017. Full-text, US-based, English language articles describing the patient perspective of SDM in oncology care were included. Relevant data from articles were reviewed in a qualitative synthesis. RESULTS: From 3435 potential citations, a total of 35 articles were included. The most common cancers studied were breast (n = 22; 62.9%) and prostate (n = 9; 25.7%). The identified themes for barriers to SDM were uncertainty in the treatment decision, concern regarding adverse effects, and poor physician communication. Themes for facilitators for SDM included physician consideration of patient preferences, positive physician actions and behaviors, and use or encouragement of support systems. CONCLUSION: As SDM gains use within oncology practice, understanding key influences will allow for more effective implementation of strategies to increase patient engagement and improve care and value in the treatment process.

Modeling Episode-Based Payments for Cancer Using Commercial Claims Data.

BACKGROUND: Innovative health care reimbursement models are gaining attention as a way to move away from a payment system that rewards quantity of service over quality of care. One such alternative payment model is episode-based payment, such as the Oncology Care Model (OCM) being piloted by the Center for Medicare & Medicaid Innovation. OBJECTIVE: To adapt the OCM methodology to a commercially insured population to understand the challenges and potential implications of implementing an episode-based payment model in a commercial health plan. METHODS: Administrative claims databases from 3 regional commercial health plans were used to identify continually eligible patients (aged ≥ 18 years) with breast cancer, lung cancer, melanoma, or chronic myelogenous leukemia (CML). Episode triggers were identified using the OCM methodology. In calculating the episode-based payments, adjustments to the OCM methodology were necessary to adapt the methodology to a commercial population, since not all Medicare data elements used in the OCM algorithm are available in commercial claims data. RESULTS: The adapted OCM-like model was applied to data from 39,967 patients with 1 of 4 cancer types. Approximately 13% of patients had at least 1 episode per year and the average number of episodes per patient per year for patients with at least 1 episode ranged from 1.42 for patients with melanoma to 1.94 for patients with CML. The percentage of total annual costs included in episodes was 49%, 60%, 34%, and 52% for breast cancer, lung cancer, melanoma, and CML, respectively. CONCLUSIONS: As health care financing shifts to alternative payment models, insurers may look to adopt episode-based payments for oncology, similar to the OCM. This study shows that implementing an OCM-like model in a commercial health plan is feasible but will require adjustments to the OCM algorithm to make it implementable and applicable to populations beyond Medicare. DISCLOSURES: This study was conducted by Magellan Rx Management with funding contributed by Novartis. Zacker is an employee of Novartis. The other authors are employed by Magellan Rx Management and have nothing to disclose.

Drug Treatment Value in a Changing Oncology Landscape: A Literature and Provider Perspective.

BACKGROUND: The U.S. health care system's transition to a value-based reimbursement model holds important implications for medical innovation, care delivery, and value-based assessments of therapeutic interventions. This transition has been especially noteworthy in oncology, with substantial ongoing changes to payer reimbursement and the provider landscape, as well as the introduction of value frameworks to guide drug treatment decision making. The implications of these changes for provider assessments of drug value and evidence needs remain unclear. OBJECTIVES: To understand provider perspectives on drug value assessment and the utility of existing oncology value frameworks by identifying (a) key value-based trends in the evolving oncology landscape, (b) provider definitions of drug value, (c) the role of existing value frameworks in provider decision making, and (d) future provider evidence needs for making value-based treatment decisions. METHODS: We conducted a literature review to identify existing oncology value frameworks and definitions of drug treatment value in oncology. Using a structured discussion guide informed by this literature review, we conducted 12 telephone-based in-depth interviews in November and December 2017 with U.S. oncology providers involved in organizational drug treatment and formulary decision making within their practices. Responses to interview questions were analyzed and reported as averages and percentages across participants. RESULTS: Of 293 publications identified by keyword searches, 35 relevant articles were identified. Among these, the literature review identified no common definition for providers to assess drug value. Interview research participants described large ongoing changes in the oncology provider landscape, with economic pressures from payers as the foremost leading factor. Although 5 value frameworks were found in the literature, interviews found that in practice few providers consider these value frameworks to be key influences when evaluating treatment or formulary decisions. Furthermore, while 83% of participants' organizations employed some form of internal clinical pathways, only the minority (25%) with pathways integrated in their electronic medical record (EMR) systems saw these pathways as significantly affecting clinicians' drug treatment decision making. To aid the ongoing shift from volume-based to value-based care, we found that, rather than value frameworks, providers are looking for patient-level tools to make more appropriate drug decisions. CONCLUSIONS: Payer reimbursement pressures are leading to radical changes in the oncology provider landscape, and there is a need for improved guidance for providers in assessing drug value. In particular, this study identifies the need for a timely and multifaceted summary of information required to assess the value of alternative treatment options for a given patient. Manufacturers also need to make significant strides to help generate and improve the dissemination of evidence to support the value of their therapies. DISCLOSURES: Funding for this work was provided by Novartis Pharmaceuticals. The study sponsor was involved in study design, data interpretation, and data review. All authors contributed to the development of the manuscript and maintained control over the final content. Sasane, Howe, Wong, and Zacker were employees of Novartis at the time of this study. Frois, Jarvis, and Grice are or have been employed by Analysis Group, which received a grant from Novartis for this research. At the time of this study, Analysis Group received funding from multiple manufacturers with oncology products in their portfolio during this time period, including, but not limited to, Astellas and Genentech.

Cost variation and savings opportunities in the Oncology Care Model.

OBJECTIVES: This study seeks to identify service categories that present the greatest opportunities to reduce spending in oncology care episodes, as defined by the CMS Oncology Care Model (OCM). Regional variation in spending for similar patients is often interpreted as evidence that resources can be saved, because higher-spending regions could achieve savings by behaving more like their lower-spending counterparts. STUDY DESIGN: We used Surveillance, Epidemiology, and End Results Medicare data from 2006-2013 for this retrospective observational cohort study. Analysis focused on patients with non-small cell lung cancer, advanced (stage III or IV) breast cancer, renal cell carcinoma, multiple myeloma, or chronic myeloid leukemia. METHODS: Episodes were identified for patients with the 5 included cancers, following the episode definition used in the OCM. We estimated standardized episode-level spending for a standard patient across subcategories of care for each hospital referral region (HRR) defined by the Dartmouth Atlas. The contribution of each subcategory to interregional variation in total spending reflects that subcategory's potential to yield savings. RESULTS: Chemotherapy and acute inpatient hospital care tended to be the highest contributors to interregional variation. Imaging, nonchemotherapy Part B drugs, physician evaluation and management services, and diagnostics were negligible contributors to interregional variation for all 5 cancers. CONCLUSIONS: Chemotherapy and inpatient hospital care offer the most potential to reduce spending within OCM-defined episodes. Other sources of savings differ by type of cancer. Assuming patient outcomes are not compromised, low-spending HRRs may be models for lowering cost in cancer care.

Share of Oncology Versus Nononcology Spending in Episodes Defined by the Centers for Medicare & Medicaid Services Oncology Care Model.

PURPOSE: Performance-based payments to oncology providers participating in the Centers for Medicare & Medicaid Services (CMS) Oncology Care Model (OCM) are based, in part, on overall spending in 6-month episodes of care, including spending unrelated to oncology care. The amount of spending likely to occur outside of oncologists' purview is unknown. METHODS: Following the OCM definition of an episode, we used SEER-Medicare data from 2006 to 2013 to identify episodes of cancer care for the following diagnoses: breast cancer (BC), non-small-cell lung cancer, renal cell carcinoma, multiple myeloma (MM), and chronic myeloid leukemia. Claims were categorized by service type and, separately, whether the content fell within the purview of oncology providers (classified as oncology, with all other claims nononcology). We calculated the shares of episode spending attributable to oncology versus nononcology services. RESULTS: The percentage of oncology spending within OCM episodes ranged from 62.4% in BC to 85.5% in MM. The largest source of oncology spending was antineoplastic drug therapy, ranging from 21.8% of total episode spending in BC to 67.6% in chronic myeloid leukemia. The largest source of nononcology spending was acute hospitalization and inpatient physician costs, ranging from 6.6% of overall spending for MM to 10.4% for non-small-cell lung cancer; inpatient oncology spending contributed roughly similar shares to overall spending. CONCLUSION: Most spending in OCM-defined episodes was attributable to services related to cancer care, especially antineoplastic drug therapy. Inability to control nononcology spending may present challenges for practices participating in the OCM, however.

Greater Spending Associated with Improved Survival for Some Cancers in OCM-Defined Episodes.

BACKGROUND: Previous research finds significant variation in spending and utilization across regions, with little evidence of differences in outcomes. While such findings have been interpreted as evidence that spending can be reduced without compromising patient outcomes, the link between spending variation and outcomes remains a critical question. OBJECTIVE: To use evidence from geographic variations in spending and an individual-level survival analysis to test whether spending within oncology care episodes is associated with survival, where episodes are defined as in the Center for Medicare and Medicaid Innovation's Oncology Care Model (OCM). METHODS: In this retrospective cohort analysis, patient data from the Surveillance, Epidemiology and End Results Medicare (SEER-Medicare) database for 2007-2013 were linked to hospital referral regions (HRRs) using ZIP codes. Patients in the SEER program are a part of selected population-based cancer registries throughout the United States whose records are linked to Medicare enrollment and claims data (93% of elderly registry patients were successfully linked to Medicare data). Episodes of cancer care were defined as in the OCM: 6 months following a triggering chemotherapy claim. We analyzed episodes of care for 5 tumor types: advanced breast cancer (BC), non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), multiple myeloma (MM), and chronic myeloid leukemia (CML). We removed the effects of differentials in Medicare payment rates, which were mostly geographic. Regression analysis was then used to calculate standardized spending levels for each HRR, that is, spending adjusted for differences in patient and episode characteristics. To examine the effect of spending during OCM-defined episodes on individual-level survival, we used Cox regression with patient characteristics and standardized HRR spending per episode as covariates. To address concerns that may arise from multiple comparisons across the 5 tumor types, we used the Benjamini-Hochberg procedure to control the false discovery rate. RESULTS: Our analysis showed significant differences in standardized spending across HRRs. Compared with spending at the 20th percentile episode, spending at the 80th percentile ranged from 25% higher ($57,392 vs. $45,995 for MM) to 47% higher ($36,920 vs. $24,127 for RCC), indicating practice style variation across regions. The hazard of dying for patients with NSCLC and MM statistically significantly decreased by 7% (HR = 0.93, P = 0.006) and 13% (HR = 0.87, P = 0.019), respectively, for a $10,000 increase in standardized spending (in 2013 U.S. dollars). For the 3 other cancers, spending effects were not statistically significant. After using the Benjamini-Hochberg procedure with a 5% false discovery rate, the effects of increased spending on improved survival for NSCLC and MM remained statistically significant. CONCLUSIONS: The association we found between spending and survival suggests caution may be warranted for physicians, pharmacists, other health care professionals, and policymakers involved in efforts to reduce across-the-board spending within OCM-defined episodes for at least 2 of the 5 cancers studied. DISCLOSURES: Funding for this research was provided by Novartis Pharmaceuticals to Precision Health Economics in support of research design, analysis, and technical writing services. The funder provided input on study design and comments on the draft report. Baumgardner, Shahabi, and Linthicum are employees of Precision Health Economics (PHE), a health care consultancy to the insurance and life science industries, including firms that market oncology therapies. Vine was an employee of PHE at the time of this research. Zacker is an employee of and shareholder in Novartis Pharmaceuticals. Lakdawalla is a consultant to PHE and holds equity in its parent company, Precision Medicine Group.

The impact of self- and physician-administered cancer treatment on work productivity and healthcare utilization.

BACKGROUND: Lost productivity in the workplace represents a significant portion of the economic burden of cancer in the United States. Cancer treatments have historically been physician-administered, while recent innovations have led to the development of self-administered, usually oral, agents. Self-administered treatments have the potential to reduce healthcare utilization and time away from work, but the magnitude of these effects is unknown. OBJECTIVE: To compare the effects of self- and physician-administered cancer treatment on work productivity and health care utilization. METHODS: Cancer subtypes with self- and physician-administered treatment options were selected. Patients with female breast, or lung or bronchus cancer diagnosed in 2004-2013 were identified in the Truven Health Analytics Commercial Claims and Encounters and Health and Productivity Management databases. Using multivariate regression models, work productivity and healthcare utilization were compared for patients receiving self- versus physician-administered treatment in the 12 months after initial diagnosis. Work productivity outcomes included the number of sick days and short-term disability claims. RESULTS: One month of self- versus physician-administered treatment significantly reduced cancer-related outpatient services, doctor visits, and infusions in the 12 months after initial diagnosis for both cancers of interest. In addition, breast and lung or bronchus cancer patients who received self-administered treatment were less likely to have short-term disability claims, and breast cancer patients with non-metastatic disease who received self-administered treatment had significantly fewer sick days. CONCLUSIONS: Self-administered cancer treatment was associated with fewer cancer-related outpatient services and reduced time away from work compared to physician-administered cancer treatment.

A Systematic Review of the Effect of Cancer Treatment on Work Productivity of Patients and Caregivers.

BACKGROUND: Cancer is a leading cause of death with substantial financial costs. While significant data exist on the economic burden of care, less is known about the indirect costs of treatment and, specifically, the effect on work productivity of patients and their caregivers. To examine the full effect of cancer and the potential value of new therapies, all aspects of care, including indirect costs and patient-reported outcomes, should be evaluated. OBJECTIVE: To perform a systematic review of the literature examining the effect of cancer treatment on work productivity in patients and their caregivers. METHODS: Articles, abstracts, and bibliographies were searched in MEDLINE, Cochrane, Scopus, CINAHL, and conference lists from the American Society of Clinical Oncology, International Society for Pharmacoeconomics and Outcomes Research, and Academy of Managed Care Pharmacy up to January 2016. The PRISMA guidelines were used. Controlled search terminology included individual pharmacologic therapies for cancer and terms related to patient and caregiver work productivity. Citations were included if they evaluated the effect of cancer treatment on work productivity, used and described productivity assessments and instruments, and were written in English. Studies that reported only clinical outcomes or assessed only nonpharmacological treatments were excluded. Identified studies were screened and extracted for study inclusion by 2 independent reviewers, with adjudication by 2 secondary reviewers during the final eligibility phase. RESULTS: Of 978 potential citations, 62 articles or abstracts were included. Forty-six studies (74.2%) evaluated patient-related productivity; 10 studies (16.1%) focused on caregivers, and 6 studies (9.7%) were a combination. Sixteen countries contributed literature, including 26 studies (41.2%) conducted in the United States. The most commonly studied cancer was breast cancer (53.2%). Nearly 22% of the studies were conducted on multiple types of cancer. The significant diversity of study methodologies and measurements rendered a single unifying conclusion difficult. A variety of metrics were used to quantify productivity (hours lost, return to work, change of status, and activity impairment). The Work Productivity and Activity Impairment questionnaire was the most commonly used standardized tool (n = 9; 14.5%). Factors found to be associated with impairment in productivity included disease- and treatment-related effects, such as disease progression and severity, cognitive and neurological impairments, poor physical and psychological status, receipt of chemotherapy, and time and expenses required to receive therapy. CONCLUSIONS: This review highlights the considerable variety of studies that have assessed work productivity for cancer treatment and the multifaceted reasons affecting patients and caregivers. With increasing emphasis being given to understanding the value that patients assign to various aspects of cancer treatment, more streamlined information on productivity may be important to patients as they play a greater role in selecting treatment goals through shared decision making with their providers. DISCLOSURES: This study was funded by Novartis Pharmaceuticals, which provided the concept, general oversight, and research collaboration on the project. Covvey and Kamal received research funding from Novartis Pharmaceuticals and the College of Psychiatric and Neurologic Pharmacists. Zacker is employed by, and owns stock in, Novartis Pharmaceuticals. A related poster abstract was presented at the Academy of Managed Care Pharmacy April 2016 Annual Meeting and published as Kamal KM, Covvey JR, Dashputre A, Ghosh S, Zacker C. A conceptual framework for valuebased oncology treatment: a societal perspective. J Manag Care Spec Pharm. 2016;22(4 Suppl A):S28. A publication-only abstract was presented at the American Society of Clinical Oncology 2016 Annual Meeting and published as Covvey JR, Kamal KM, Dashputre A, Ghosh S, Zacker C. The impact of cancer treatment on work productivity of patients and caregivers: a systematic review of the evidence. J Clin Oncol. 2016;34(Suppl):e18249. Study concept and design were contributed by Zacker, Kamal, and Covvey. Dashputre and Ghosh took the lead in data collection, along with Kamal and Covvey, and data interpretation was performed primarily by Shah and Bhosle, along with Ghosh, Dashputre, Covvey, and Kamal. The manuscript was written by Kamal, Covvey, Shah, and Bhosle and revised primarily by Zacker, along with Shah, Bhosle, Kamal, and Covvey.