Cancer Drug Wastage and Mitigation Methods: A Systematic Review.

OBJECTIVES: To systematically review published evidence on cancer drug wastage and the effectiveness of mitigation methods. METHODS: Search keywords for Scopus, PubMed, and EMBASE were developed using the Pearl Growing technique. Relevant articles were identified in a two-step process: first based on titles/abstracts, then on full article reviews. Among the identified English peer-reviewed articles, those considering adults ≥18 years and relevant cancer drug wastage outcomes were included. Key concepts and measures for drug wastage and its mitigation were tabulated. Trends in publication numbers were analyzed using Mann-Kendall tests. Costs were converted first to 2024 local currencies using country-wise consumer price indexes, and then to 2024 USD using exchange rates. RESULTS: Among 6,298 unique articles, 94 met the inclusion criteria. Seventy-four (79%) of these were published since 2015, highlighting increasing attention to cancer drug wastage. Twenty-three articles (24%) explicitly reported drug wastage amounts, whereas fifty-two articles (55%) considered the mitigation methods. Most articles focused on high-income countries (n=67), single hospital settings (n=45), and retrospective study designs (n=55). Wastage mitigation techniques included vial-sharing (n=21), dose-rounding (n=17), closed-system transfer device (n=9), centralized drug preparation (n=7), and vial size optimization (n=7). A trend towards higher median wastage cost was evident in US settings ($135.35/patient-month) compared to other countries ($37.71/patient-month)), while mitigation methods across countries were not statistically significant. CONCLUSIONS: High cancer drug costs highlight the importance of minimizing drug wastage to reduce healthcare expenditure. Our review demonstrates that wastage varies by healthcare setting and mitigation technique. Future studies would benefit from reporting standards for cancer drug wastage that include reporting wastage (both in mg and cost, preferably in terms of Purchase Power Parity), as well as cohort size, considered vial sizes, considered dosages, and employed mitigation methods separately for each drug. This approach would account for variability in cancer drug wastage and help identify optimal mitigation practices tailored to the health system context.

Determining optimal COVID-19 testing center locations and capacities.

We study the problem of determining the locations and capacities of COVID-19 specimen collection centers to efficiently improve accessibility to polymerase chain reaction testing during surges in testing demand. We develop a two-echelon multi-period location and capacity allocation model that determines optimal number and locations of pop-up testing centers, capacities of the existing centers as well as assignments of demand regions to these centers, and centers to labs. The objective is to minimize the total number of delayed appointments and specimens subject to budget, capacity, and turnaround time constraints, which will in turn improve the accessibility to testing. We apply our model to a case study for locating COVID-19 testing centers in the Region of Waterloo, Canada using data from the Ontario Ministry of Health, public health databases, and medical literature. We also test the performance of the model under uncertain demand and analyze its outputs under various scenarios. Our analyses provide practical insights to the public health decision-makers on the timing of capacity expansions and the locations for the new pop-up centers. According to our results, the optimal strategy is to dynamically expand the existing specimen collection center capacities and prevent bottlenecks by locating pop-up facilities. The optimal locations of pop-ups are among the densely populated areas that are in proximity to the lab and a subset of those locations are selected with the changes in demand. A comparison with a static approach promises up to 39% cost savings under high demand using the developed multi-period model.

Tollgate-based progression pathways of ALS patients.

OBJECTIVE: To capture ALS progression in arm, leg, speech, swallowing, and breathing segments using a disease-specific staging system, namely tollgate-based ALS staging system (TASS), where tollgates refer to a set of critical clinical events including having slight weakness in arms, needing a wheelchair, needing a feeding tube, etc. METHODS: We compiled a longitudinal dataset from medical records including free-text clinical notes of 514 ALS patients from Mayo Clinic, Rochester-MN. We derived tollgate-based progression pathways of patients up to a 1-year period starting from the first clinic visit. We conducted Kaplan-Meier analyses to estimate the probability of passing each tollgate over time for each functional segment. RESULTS: At their first clinic visit, 93%, 77%, and 60% of patients displayed some level of limb, bulbar, and breathing weakness, respectively. The proportion of patients at milder tollgate levels (tollgate level < 2) was smaller for arm and leg segments (38% and 46%, respectively) compared to others (> 65%). Patients showed non-uniform TASS pathways, i.e., the likelihood of passing a tollgate differed based on the affected segments at the initial visit. For instance, stratified by impaired segments at the initial visit, patients with limb and breathing impairment were more likely (62%) to use bi-level positive airway pressure device in a year compared to those with bulbar and breathing impairment (26%). CONCLUSION: Using TASS, clinicians can inform ALS patients about their individualized likelihood of having critical disabilities and assistive-device needs (e.g., being dependent on wheelchair/ventilation, needing walker/wheelchair or communication devices), and help them better prepare for future.