Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research.

OBJECTIVE: Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening. METHODS: This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms. RESULTS AND CONCLUSIONS: The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

Risk Prediction Using Bayesian Networks: An Immunotherapy Case Study in Patients With Metastatic Renal Cell Carcinoma.

PURPOSE: To address the need for more accurate risk stratification models for cancer immuno-oncology, this study aimed to develop a machine-learned Bayesian network model (BNM) for predicting outcomes in patients with metastatic renal cell carcinoma (mRCC) being treated with immunotherapy. METHODS: Patient-level data from the randomized, phase III CheckMate 025 clinical trial comparing nivolumab with everolimus for second-line treatment in patients with mRCC were used to develop the BNM. Outcomes of interest were overall survival (OS), all-cause adverse events, and treatment-related adverse events (TRAE) over 36 months after treatment initiation. External validation of the model's predictions for OS was conducted using data from select centers from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC). RESULTS: Areas under the receiver operating characteristic curve (AUCs) for BNM-based classification of OS using baseline data were 0.74, 0.71, and 0.68 over months 12, 24, and 36, respectively. AUC for OS at 12 months increased to 0.86 when treatment response and progression status in year 1 were included as predictors; progression and response at 12 months were highly prognostic of all outcomes over the 36-month period. AUCs for adverse events and treatment-related adverse events were approximately 0.6 at 12 months but increased to approximately 0.7 by 36 months. Sensitivity analysis comparing the BNM with machine learning classifiers showed comparable performance. Test AUC on IMDC data for 12-month OS was 0.71 despite several variable imbalances. Notably, the BNM outperformed the IMDC risk score alone. CONCLUSION: The validated BNM performed well at prediction using baseline data, particularly with the inclusion of response and progression at 12 months. Additionally, the results suggest that 12 months of follow-up data alone may be sufficient to inform long-term survival projections in patients with mRCC.

Current challenges for assessing the long-term clinical benefit of cancer immunotherapy: a multi-stakeholder perspective.

Immuno-oncologics (IOs) differ from chemotherapies as they prime the patient's immune system to attack the tumor, rather than directly destroying cancer cells. The IO mechanism of action leads to durable responses and prolonged survival in some patients. However, providing robust evidence of the long-term benefits of IOs at health technology assessment (HTA) submission presents several challenges for manufacturers. The aim of this article was to identify, analyze, categorize, and further explore the key challenges that regulators, HTA agencies, and payers commonly encounter when assessing the long-term benefits of IO therapies. Insights were obtained from an international, multi-stakeholder steering committee (SC) and expert panels comprising of payers, economists, and clinicians. The selected individuals were tasked with developing a summary of challenges specific to IOs in demonstrating their long-term benefits at HTA submission. The SC and expert panels agreed that standard methods used to assess the long-term benefit of anticancer drugs may have limitations for IO therapies. Three key areas of challenges were identified: (1) lack of a disease model that fully captures the mechanism of action and subsequent patient responses; (2) estimation of longer-term outcomes, including a lack of agreement on ideal methods of survival analyses and extrapolation of survival curves; and (3) data limitations at the time of HTA submission, for which surrogate survival end points and real-world evidence could prove useful. A summary of the key challenges facing manufacturers when submitting evidence at HTA submission was developed, along with further recommendations for manufacturers in what evidence to produce. Despite almost a decade of use, there remain significant challenges around how best to demonstrate the long-term benefit of checkpoint inhibitor-based IOs to HTA agencies, clinicians, and payers. Manufacturers can potentially meet or mitigate these challenges with a focus on strengthening survival analysis methodology. Approaches to doing this include identifying reliable biomarkers, intermediate and surrogate end points, and the use of real-world data to inform and validate long-term survival projections. Wider education across all stakeholders-manufacturers, payers, and clinicians-in considering the long-term survival benefit with IOs is also important.

Cost-effectiveness of pembrolizumab versus brentuximab vedotin for patients with relapsed or refractory classical Hodgkin's lymphoma: a United States payer perspective.

AIMS: Patients with classical Hodgkin's lymphoma (cHL) who have relapsed after or are ineligible for autologous stem cell transplantation (ASCT) have limited treatment options and generally a poor prognosis. Pembrolizumab was recently approved in the US for the treatment of such patients having demonstrated clinical benefit and tolerability in relapsed/refractory cHL; however, the cost-effectiveness of pembrolizumab in this population is currently unknown. MATERIALS AND METHODS: A three-state Markov model (progression-free [PF], progressed disease, and death) was developed to assess the cost-effectiveness of pembrolizumab (200 mg) vs brentuximab vedotin (BV; 1.8 mg/kg) in patients with relapsed/refractory cHL after ASCT who have not received BV post-ASCT over a 20-year time horizon from a US payer perspective. PF survival was modeled using a naïve indirect treatment comparison of data from KEYNOTE-087 and the SG035-003 trial. Post-progression survival was modeled using data from published literature. Costs (drug acquisition and administration, disease management, subsequent treatment, and adverse events) and outcomes were discounted at an annual rate of 3.0%. Uncertainty surrounding cost-effectiveness was assessed via probabilistic, deterministic, and scenario analyses. RESULTS: In the base case, pembrolizumab was predicted to yield an additional 0.574 life-years (LYs) and 0.500 quality-adjusted life-years (QALYs) vs BV and cost savings of $63,278. Drug acquisition costs were the biggest driver of incremental costs between strategies. Pembrolizumab had a 99.6% probability of being cost-effective compared with BV at a willingness-to-pay threshold of $20,000/QALY and dominated BV in all scenarios tested. LIMITATIONS: The analysis was subject to potential bias due to the use of a naïve indirect treatment comparison and, given the current immaturity of OS in KEYNOTE-087, PPS was assumed equivalent across both treatments. CONCLUSION: Pembrolizumab is a cost-effective alternative to BV for patients with relapsed/refractory cHL after ASCT.

Pembrolizumab versus the standard of care for relapsed and refractory classical Hodgkin's lymphoma progressing after brentuximab vedotin: an indirect treatment comparison.

BACKGROUND: There is significant unmet need among patients with relapsed and refractory classical Hodgkin's lymphoma (RRcHL) who have failed multiple lines of therapy, including brentuximab vedotin (BV). Pembrolizumab, an immune checkpoint inhibitor, is one possible treatment solution for this population. RESEARCH METHODS: The objective of this study was to compare progression-free survival (PFS) with standard of care (SOC) versus pembrolizumab in previously BV treated RRcHL patients. A systematic literature review identified one observational study of SOC that was suitable for comparison with KEYNOTE-087, the principal trial of pembrolizumab in this population. Both naïve and population-adjusted (using outcomes regression) pairwise indirect comparisons were conducted. The primary analysis included all patients who had failed BV, with a secondary analysis conducted including only those known to have failed BV that was part of definitive treatment. RESULTS: In the primary analysis, SOC was inferior to pembrolizumab in both the unadjusted comparison (HR 5.00 [95% confidence interval (CI) 3.56-7.01]) and the adjusted comparison (HR 6.35 [95% CI 4.04-9.98]). These HRs increased to 5.16 (95% CI 3.61-7.38) and 6.56 (95% CI 4.01-10.72), respectively, in the secondary analysis. CONCLUSION: Pembrolizumab offers a significant improvement in PFS compared to SOC in this population.

High intensity lifestyle intervention and long-term impact on weight and clinical outcomes.

BACKGROUND: Obesity increases the risk for diabetes and cardiovascular events, with a corresponding growth in medical costs. High intensity lifestyle intervention (HILI) is the cornerstone for weight management. We assessed the effectiveness of clinic-based HILI on weight loss and associated clinical outcomes by duration of program participation and comorbid conditions. METHODS: This was a retrospective cohort study of patients who enrolled in HILI weight management programs at Health Management Resources (HMR) clinics located across the U.S. Patients completed health risk assessments (HRA) and were enrolled for up to 24 months at the time of follow-up HRA. HMR programs provide weekly group coaching to achieve reduced calorie intake, increased fruit/vegetable intake, and physical activity ≥2,000 kcal/wk. A Markov model predicted avoidance of diabetes and cardiovascular events and projected cost savings due to weight loss. RESULTS: Of the 500 patients included in the analysis, 67% were female and mean age was 54.1 years (s.d. 11.6). The baseline weight and BMI were 243.5 lbs (range 144.0-545.0) and 38.8 kg/m2 (range 25.4-85.0), respectively. Overall, patients lost an average of 47.4 lbs (18.9% of initial body weight [IBW]); the amount of weight loss was consistent among those with diabetes/pre-diabetes (50%), high/moderate risk for dyslipidemia (60%), hypertension/pre-hypertension (86%), and severe obesity (37%). The mean IBW lost was 16.4%, 19.3%, 20.7% for ≤6 months (n = 165), 7-12 months (n = 140), 13-24 months (n = 195) of program participation, respectively. The simulation model estimated 22 diabetes and 30 cardiovascular events and $1,992,370 medical costs avoided over 5 years in the 500 patients evaluated. CONCLUSION: Patients in the HMR clinic-based HILI program achieved substantial weight loss regardless of duration of program participation, risk profile and comorbid status. The HMR program could be an effective strategy to prevent costly diabetes and cardiovascular events, particularly in high risk patients.

MicroRNA-302/367 cluster governs hESC self-renewal by dually regulating cell cycle and apoptosis pathways.

miR-302/367 is the most abundant miRNA cluster in human embryonic stem cells (hESCs) and can promote somatic cell reprogramming. However, its role in hESCs remains poorly understood. Here, we studied functional roles of the endogenous miR-302/367 cluster in hESCs by employing specific TALE-based transcriptional repressors. We revealed that miR-302/367 cluster dually regulates hESC cell cycle and apoptosis in dose-dependent manner. Gene profiling and functional studies identified key targets of the miR-302/367 cluster in regulating hESC self-renewal and apoptosis. We demonstrate that in addition to its role in cell cycle regulation, miR-302/367 cluster conquers apoptosis by downregulating BNIP3L/Nix (a BH3-only proapoptotic factor) and upregulating BCL-xL expression. Furthermore, we show that butyrate, a natural compound, upregulates miR-302/367 cluster expression and alleviates hESCs from apoptosis induced by knockdown of miR-302/367 cluster. In summary, our findings provide new insights in molecular mechanisms of how miR-302/367 cluster regulates hESCs.

A multicolor panel of TALE-KRAB based transcriptional repressor vectors enabling knockdown of multiple gene targets.

Stable and efficient knockdown of multiple gene targets is highly desirable for dissection of molecular pathways. Because it allows sequence-specific DNA binding, transcription activator-like effector (TALE) offers a new genetic perturbation technique that allows for gene-specific repression. Here, we constructed a multicolor lentiviral TALE-Kruppel-associated box (KRAB) expression vector platform that enables knockdown of multiple gene targets. This platform is fully compatible with the Golden Gate TALEN and TAL Effector Kit 2.0, a widely used and efficient method for TALE assembly. We showed that this multicolor TALE-KRAB vector system when combined together with bone marrow transplantation could quickly knock down c-kit and PU.1 genes in hematopoietic stem and progenitor cells of recipient mice. Furthermore, our data demonstrated that this platform simultaneously knocked down both c-Kit and PU.1 genes in the same primary cell populations. Together, our results suggest that this multicolor TALE-KRAB vector platform is a promising and versatile tool for knockdown of multiple gene targets and could greatly facilitate dissection of molecular pathways.