Assessing the Environmental and Downstream Human Health Impacts of Decentralizing Cancer Care.

Importance: Greenhouse gas (GHG) emissions from health care are substantial and disproportionately harm persons with cancer. Emissions from a central component of oncology care, outpatient clinician visits, are not well described, nor are the reductions in emissions and human harms that could be obtained through decentralizing this aspect of cancer care (ie, telemedicine and local clinician care when possible). Objective: To assess potential reductions in GHG emissions and downstream health harms associated with telemedicine and fully decentralized cancer care. Design, Setting, and Participants: This population-based cohort study and counterfactual analyses using life cycle assessment methods analyzed persons receiving cancer care at Dana-Farber Cancer Institute between May 2015 and December 2020 as well as persons diagnosed with cancer over the same period from the Cancer in North America (CiNA) public dataset. Data were analyzed from October 2023 to April 2024. Main Outcomes and Measures: The adjusted per-visit day difference in GHG emissions in kilograms of carbon dioxide (CO2) equivalents between 2 periods: an in-person care model period (May 2015 to February 2020; preperiod) and a telemedicine period (March to December 2020; postperiod), and the annual decrease in disability-adjusted life-years in a counterfactual model where care during the preperiod was maximally decentralized nationwide. Results: Of 123 890 included patients, 73 988 (59.7%) were female, and the median (IQR) age at first diagnosis was 59 (48-68) years. Patients were seen over 1.6 million visit days. In mixed-effects log-linear regression, the mean absolute reduction in per-visit day CO2 equivalent emissions between the preperiod and postperiod was 36.4 kg (95% CI, 36.2-36.6), a reduction of 81.3% (95% CI, 80.8-81.7) compared with the baseline model. In a counterfactual decentralized care model of the preperiod, there was a relative emissions reduction of 33.1% (95% CI, 32.9-33.3). When demographically matched to 10.3 million persons in the CiNA dataset, decentralized care would have reduced national emissions by 75.3 million kg of CO2 equivalents annually; this corresponded to an estimated annual reduction of 15.0 to 47.7 disability-adjusted life-years. Conclusions and Relevance: This cohort study found that using decentralization through telemedicine and local care may substantially reduce cancer care's GHG emissions; this corresponds to small reductions in human mortality.

Perspectives of Oncologists on the Ethical Implications of Using Artificial Intelligence for Cancer Care.

Importance: Artificial intelligence (AI) tools are rapidly integrating into cancer care. Understanding stakeholder views on ethical issues associated with the implementation of AI in oncology is critical to optimal deployment. Objective: To evaluate oncologists' views on the ethical domains of the use of AI in clinical care, including familiarity, predictions, explainability (the ability to explain how a result was determined), bias, deference, and responsibilities. Design, Setting, and Participants: This cross-sectional, population-based survey study was conducted from November 15, 2022, to July 31, 2023, among 204 US-based oncologists identified using the National Plan & Provider Enumeration System. Main Outcomes and Measures: The primary outcome was response to a question asking whether participants agreed or disagreed that patients need to provide informed consent for AI model use during cancer treatment decisions. Results: Of 387 surveys, 204 were completed (response rate, 52.7%). Participants represented 37 states, 120 (63.7%) identified as male, 128 (62.7%) as non-Hispanic White, and 60 (29.4%) were from academic practices; 95 (46.6%) had received some education on AI use in health care, and 45.3% (92 of 203) reported familiarity with clinical decision models. Most participants (84.8% [173 of 204]) reported that AI-based clinical decision models needed to be explainable by oncologists to be used in the clinic; 23.0% (47 of 204) stated they also needed to be explainable by patients. Patient consent for AI model use during treatment decisions was supported by 81.4% of participants (166 of 204). When presented with a scenario in which an AI decision model selected a different treatment regimen than the oncologist planned to recommend, the most common response was to present both options and let the patient decide (36.8% [75 of 204]); respondents from academic settings were more likely than those from other settings to let the patient decide (OR, 2.56; 95% CI, 1.19-5.51). Most respondents (90.7% [185 of 204]) reported that AI developers were responsible for the medico-legal problems associated with AI use. Some agreed that this responsibility was shared by physicians (47.1% [96 of 204]) or hospitals (43.1% [88 of 204]). Finally, most respondents (76.5% [156 of 204]) agreed that oncologists should protect patients from biased AI tools, but only 27.9% (57 of 204) were confident in their ability to identify poorly representative AI models. Conclusions and Relevance: In this cross-sectional survey study, few oncologists reported that patients needed to understand AI models, but most agreed that patients should consent to their use, and many tasked patients with choosing between physician- and AI-recommended treatment regimens. These findings suggest that the implementation of AI in oncology must include rigorous assessments of its effect on care decisions as well as decisional responsibility when problems related to AI use arise.

Autologous Skin Cell Suspension for Full-Thickness Skin Defect Reconstruction: Current Evidence and Health Economic Expectations.

Despite differing etiologies, acute thermal burn injuries and full-thickness (FT) skin defects are associated with similar therapeutic challenges. When not amenable to primary or secondary closure, the conventional standard of care (SoC) treatment for these wound types is split-thickness skin grafting (STSG). This invasive procedure requires adequate availability of donor skin and is associated with donor site morbidity, high healthcare resource use (HCRU), and costs related to prolonged hospitalization. As such, treatment options that can facilitate effective healing and donor skin sparing have been highly anticipated. The RECELL® Autologous Cell Harvesting Device facilitates preparation of an autologous skin cell suspension (ASCS) for the treatment of acute thermal burns and FT skin defects. In initial clinical trials, the approach showed superior donor skin-sparing benefits and comparable wound healing to SoC STSG among patients with acute thermal burn injuries. These findings led to approval of RECELL for this indication by the US Food and Drug Administration (FDA) in 2018. Subsequent clinical evaluation in non-thermal FT skin wounds showed that RECELL, when used in combination with widely meshed STSG, provides donor skin-sparing advantages and comparable healing outcomes compared with SoC STSG. As a result, the device received FDA approval in June of 2023 for treatment of FT skin defects caused by traumatic avulsion or surgical excision or resection. Given that health economic advantages have been demonstrated for RECELL ± STSG versus STSG alone when used for burn therapy, it is prudent to examine similarities in the burn and FT skin defect treatment pathways to forecast the potential health economic advantages for RECELL when used in FT skin defects. This article discusses the parallels between the two indications, the clinical outcomes reported for RECELL, and the HCRU and cost benefits that may be anticipated with use of the device for non-thermal FT skin defects.

Use, variability, and justification of eligibility criteria for phase II and III clinical trials in acute leukemia.

Clinical trial eligibility criteria can unfairly exclude patients or unnecessarily expose them to known risks if criteria are not concordant with drug safety. There are few data evaluating the extent to which acute leukemia eligibility criteria are justified. We analyzed criteria and drug safety data for front-line phase II and/or III acute leukemia trials with start dates 1/1/2010-12/31/2019 registered on clinicaltrials.gov. Multivariable analyses assessed concordance between criteria use and safety data (presence of criteria with a safety signal, or absence of criteria without a signal), and differences between criteria and safety-based limits. Of 250 eligible trials, concordant use of ejection fraction criteria was seen in 34.8%, corrected QT level (QTc) in 22.4%, bilirubin in 68.4%, aspartate transaminase/alanine aminotransferase (AST/ALT) in 58.8%, renal function in 68.4%, human immunodeficiency virus (HIV) in 54.8%, and hepatitis B and C in 42.0% and 41.2%. HIV and hepatitis B and C criteria use was concordant with safety data (adjusted Odds Ratios 2.04 [95%CI: 1.13, 3.66], 2.64 [95%CI: 1.38, 5.04], 2.27 [95%CI: 1.20, 4.32]) but organ function criteria were not (all P>0.05); phase III trials were not more concordant. Bilirubin criteria limits were the same as safety-based limits in 16.0% of trials, AST/ALT in 18.1%, and renal function in 13.9%; in 75.7%, 51.4%, and 56.5% of trials, criteria were more restrictive, respectively, by median differences of 0.2, 0.5, and 0.5 times the upper limits of normal. We found limited drug safety justifications for acute leukemia eligibility criteria. These data define criteria use and limits that can be rationally modified to increase patient inclusion and welfare.

Sociodemographic associations with uptake of novel therapies for acute myeloid leukemia.

Inequitable uptake of novel therapies (NT) in non-cancer settings are known for patients with lower socioeconomic status (SES), People of Color (POC), and older adults. NT uptake equity in acute myeloid leukemia (AML) is not well known. We performed a retrospective cohort study (1/2014-8/2022) of the United States nationwide Flatiron HealthTM electronic health record-derived, de-identified database. We estimated sociodemographic associations with AML NT receipt using incidence rate ratios (IRR). Odds ratios (OR) assessed differences in venetoclax (the most common NT) receipt at community sites and between site characteristics and NT adoption. Of 8081 patients (139 sites), 3102 (38%) received a NT. NT use increased annually (IRR 1.14, 95% confidence interval [1.07, 1.22]). NT receipt was similar between Non-Hispanic-Whites and POC (IRR 1.03, [0.91, 1.17]) and as age increased (IRR 1.02 [0.97, 1.07]). At community sites, Non-Hispanic-Whites were less likely to receive venetoclax (OR 0.77 [0.66, 0.91]); older age (OR 1.05 [1.04, 1.05]) and higher area-level SES were associated with venetoclax receipt (OR 1.23 [1.05, 1.43]). Early NT adopting sites had more prescribing physicians (OR 1.25 [1.13, 1.43]) and higher SES strata patients (OR 2.81 [1.08, 7.66]). Inequities in AML NT uptake were seen by SES; for venetoclax, differential uptake reflects its label indication for older adults and those with comorbidities.

Analysis of real-world length of stay data and costs associated with use of autologous skin cell suspension for the treatment of small burns in U.S. centers.

BACKGROUND: Autologous skin cell suspension (ASCS) is a treatment for acute thermal burn injuries associated with significantly lower donor skin requirements than conventional split-thickness skin grafts (STSG). Projections using the BEACON model suggest that among patients with small burns (total body surface area [TBSA]<20 %), use of ASCS± STSG leads to a shorter length of stay (LOS) in hospital and cost savings compared with use of STSG alone. This study evaluated whether data from real-world clinical practice corroborate these findings. MATERIALS AND METHODS: Electronic medical record data were collected from January 2019 through August 2020 from 500 healthcare facilities in the United States. Adult patients receiving inpatient treatment with ASCS± STSG for small burns were identified and matched to patients receiving STSG using baseline characteristics. LOS was assumed to cost $7554/day and to account for 70 % of overall costs. Mean LOS and costs were calculated for the ASCS± STSG and STSG cohorts. RESULTS: A total of 151 ASCS± STSG and 2243 STSG cases were identified; 63.0 % of patients were male and the average age was 44.2 years. Sixty-three matches were made between cohorts. LOS was 18.5 days with ASCS± STSG and 20.6 days with STSG (difference: 2.1 days [10.2 %]). This difference led to bed cost savings of $15,587.62 per ASCS± STSG patient. Overall cost savings with ASCS± STSG were $22,268.03 per patient. CONCLUSIONS: Analysis of real-world data shows that treatment of small burn injuries with ASCS± STSG provides reduced LOS and substantial cost savings compared with STSG, supporting the validity of the BEACON model projections.

Length of Stay and Costs with Autologous Skin Cell Suspension Versus Split-Thickness Skin Grafts: Burn Care Data from US Centers.

INTRODUCTION: Autologous skin cell suspension (ASCS) significantly reduces donor skin requirements versus conventional split-thickness skin grafts (STSG) for thermal burn treatment. In analyses using the Burn-medical counter measure Effectiveness Assessment Cost Outcomes Nexus (BEACON) model, ASCS was associated with shorter hospital length of stay (LOS) and cost savings versus STSG. This study hypothesized that daily practice data from the USA would support these findings. METHODS: Electronic medical record data from 500 healthcare facilities (January 2019-August 2020) were used to match adult patients who received inpatient burn treatment with ASCS (± STSG) to patients treated with STSG alone on the basis of sex, age, percent total body surface area (TBSA), and comorbidities. Based on BEACON analyses, LOS was assumed to represent 70% of total costs and used as a proxy to assess the data. Mean LOS, costs, and the incremental revenue associated with inpatient capacity changes were calculated. RESULTS: A total of 151 ASCS and 2443 STSG patients were identified: 63.0% were male and average age was 44.5 years. Eight-one matches were made between cohorts. LOS was 21.7 days with ASCS and 25.0 days with STSG alone (difference 3.3 days [13.2%]). LOS was lower with ASCS than STSG in four of five TBSA intervals. The LOS difference led to hospital bed cost savings of $25,864 per ASCS patient; overall cost savings were $36,949 per patient. Similar cost savings were observed in TBSA groupings < 20% and ≥ 20%. The reduced LOS with ASCS translated into an increased capacity of 2.2 inpatients/bed annually, which increased hospital revenue by $92,283/burn unit bed annually. CONCLUSIONS: Real-world data show that ASCS (± STSG) is associated with reduced LOS and cost savings versus STSG alone across all burn sizes, supporting the validity of the BEACON analyses. ASCS use may also increase patient capacity and throughput, leading to increased hospital revenue.

Autologous skin cell suspension (ASCS) is a treatment for thermal skin burn injuries that can be used alone or in combination with split-thickness skin grafts (STSG), the conventional standard of care. Projections using the Burn-medical counter measure Effectiveness Assessment Cost Outcomes Nexus (BEACON) model indicate that ASCS leads to shorter hospital length of stay (LOS) and overall cost savings compared with STSG alone. These model findings are supported by benchmarking study data from a limited sample of US burn centers. The current study aimed to understand whether the BEACON projections are supported by daily clinical practice data from US healthcare facilities. Using electronic medical record data, we matched patients who received ASCS ± STSG from January 2019 to August 2020 to those receiving STSG alone on the basis of demographic and clinical factors. Data analysis showed that hospital LOS was shorter (3.3 days) with ASCS ± STSG than STSG alone, a difference associated with a hospital bed cost savings of $25,864 per ASCS patient. Overall cost savings, which included nursing time and other costs, were $36,949 per patient. Analysis of patients with burns comprising total body surface areas less than 20% or at least 20% showed cost savings in both groups. The reduced LOS with ASCS also translated into the ability to treat 2.2 more patients per hospital bed per year, which was projected to increase hospital earnings. These real-world findings support those of modeling analyses, indicating that use of ASCS ± STSG is associated with meaningful clinical and economic benefits compared with use of STSG alone.

Experimental design of the Effects of Dehydroepiandrosterone in Pulmonary Hypertension (EDIPHY) trial.

Pulmonary arterial hypertension (PAH) remains life-limiting despite numerous approved vasodilator therapies. Right ventricular (RV) function determines outcome in PAH but no treatments directly target RV adaptation. PAH is more common in women, yet women have better RV function and survival as compared to men with PAH. Lower levels of the adrenal steroid dehydroepiandrosterone (DHEA) and its sulfate ester are associated with more severe pulmonary vascular disease, worse RV function, and mortality independent of other sex hormones in men and women with PAH. DHEA has direct effects on nitric oxide (NO) and endothelin-1 (ET-1) synthesis and signaling, direct antihypertrophic effects on cardiomyocytes, and mitigates oxidative stress. Effects of Dehydroepiandrosterone in Pulmonary Hypertension (EDIPHY) is an on-going randomized double-blind placebo-controlled crossover trial of DHEA in men (n = 13) and pre- and post-menopausal women (n = 13) with Group 1 PAH funded by the National Heart, Lung and Blood Institute. We will determine whether orally administered DHEA 50 mg daily for 18 weeks affects RV longitudinal strain measured by cardiac magnetic resonance imaging, markers of RV remodeling and oxidative stress, NO and ET-1 signaling, sex hormone levels, other PAH intermediate end points, side effects, and safety. The crossover design will elucidate sex-based phenotypes in PAH and whether active treatment with DHEA impacts NO and ET-1 biosynthesis. EDIPHY is the first clinical trial of an endogenous sex hormone in PAH. Herein we present the study's rationale and experimental design.

SCANPS: a web server for iterative protein sequence database searching by dynamic programing, with display in a hierarchical SCOP browser.

SCANPS performs iterative profile searching similar to PSI-BLAST but with full dynamic programing on each cycle and on-the-fly estimation of significance. This combination gives good sensitivity and selectivity that outperforms PSI-BLAST in domain-searching benchmarks. Although computationally expensive, SCANPS exploits onchip parallelism (MMX and SSE2 instructions on Intel chips) as well as MPI parallelism to give acceptable turnround times even for large databases. A web server developed to run SCANPS searches is now available at http://www.compbio.dundee.ac.uk/www-scanps. The server interface allows a range of different protein sequence databases to be searched including the SCOP database of protein domains. The server provides the user with regularly updated versions of the main protein sequence databases and is backed up by significant computing resources which ensure that searches are performed rapidly. For SCOP searches, the results may be viewed in a new tree-based representation that reflects the structure of the SCOP hierarchy; this aids the user in placing each hit in the context of its SCOP classification and understanding its relationship to other domains in SCOP.

A comparison of SCOP and CATH with respect to domain-domain interactions.

The analysis and prediction of protein-protein interaction sites from structural data are restricted by the limited availability of structural complexes that represent the complete protein-protein interaction space. The domain classification schemes CATH and SCOP are normally used independently in the analysis and prediction of protein domain-domain interactions. In this article, the effect of different domain classification schemes on the number and type of domain-domain interactions observed in structural data is systematically evaluated for the SCOP and CATH hierarchies. Although there is a large overlap in domain assignments between SCOP and CATH, 23.6% of CATH interfaces had no SCOP equivalent and 37.3% of SCOP interfaces had no CATH equivalent in a nonredundant set. Therefore, combining both classifications gives an increase of between 23.6 and 37.3% in domain-domain interfaces. It is suggested that if possible, both domain classification schemes should be used together, but if only one is selected, SCOP provides better coverage than CATH. Employing both SCOP and CATH reduces the false negative rate of predictive methods, which employ homology matching to structural data to predict protein-protein interaction by an estimated 6.5%.

SNAPPI-DB: a database and API of Structures, iNterfaces and Alignments for Protein-Protein Interactions.

SNAPPI-DB, a high performance database of Structures, iNterfaces and Alignments of Protein-Protein Interactions, and its associated Java Application Programming Interface (API) is described. SNAPPI-DB contains structural data, down to the level of atom co-ordinates, for each structure in the Protein Data Bank (PDB) together with associated data including SCOP, CATH, Pfam, SWISSPROT, InterPro, GO terms, Protein Quaternary Structures (PQS) and secondary structure information. Domain-domain interactions are stored for multiple domain definitions and are classified by their Superfamily/Family pair and interaction interface. Each set of classified domain-domain interactions has an associated multiple structure alignment for each partner. The API facilitates data access via PDB entries, domains and domain-domain interactions. Rapid development, fast database access and the ability to perform advanced queries without the requirement for complex SQL statements are provided via an object oriented database and the Java Data Objects (JDO) API. SNAPPI-DB contains many features which are not available in other databases of structural protein-protein interactions. It has been applied in three studies on the properties of protein-protein interactions and is currently being employed to train a protein-protein interaction predictor and a functional residue predictor. The database, API and manual are available for download at: http://www.compbio.dundee.ac.uk/SNAPPI/downloads.jsp.

Biological units and their effect upon the properties and prediction of protein-protein interactions.

Structural data as collated in the Protein Data Bank (PDB) have been widely applied in the study and prediction of protein-protein interactions. However, since the basic PDB Entries contain only the contents of the asymmetric unit rather than the biological unit, some key interactions may be missed by analysing only the PDB Entry. A total of 69,054 SCOP (Structural Classification of Proteins) domains were examined systematically to identify the number of additional novel interacting domain pairs and interfaces found by considering the biological unit as stored in the PQS (Protein Quaternary Structure) database. The PQS data adds 25,965 interacting domain pairs to those seen in the PDB Entries to give a total of 61,783 redundant interacting domain pairs. Redundancy filtering at the level of the SCOP family shows PQS to increase the number of novel interacting domain-family pairs by 302 (13.3%) from 2277, but only 16/302 (1.4%) of the interacting domain pairs have the two domains in different SCOP families. This suggests the biological units add little to the elucidation of novel biological interaction networks. However, when the orientation of the domain pairs is considered, the PQS data increases the number of novel domain-domain interfaces observed by 1455 (34.5%) to give 5677 non-redundant domain-domain interfaces. In all, 162/1455 novel domain-domain interfaces are between domains from different families, an increase of 8.9% over the PDB Entries. Overall, the PQS biological units provide a rich source of novel domain-domain interfaces that are not seen in the studied PDB Entries, and so PQS domain-domain interaction data should be exploited wherever possible in the analysis and prediction of protein-protein interactions.