Nanotechnology for colorectal cancer detection and treatment

Colorectal cancer (CRC) is the third most diagnosed cancer and the second leading cause of cancer-related mortality in the United States. Across the globe, people in the age group older than 50 are at a higher risk of CRC. Genetic and environmental risk factors play a significant role in the development of CRC. If detected early, CRC is preventable and treatable. Currently, available screening methods and therapies for CRC treatment reduce the incidence rate among the population, but the micrometastasis of cancer may lead to recurrence. Therefore, the challenge is to develop an alternative therapy to overcome this complication. Nanotechnology plays a vital role in cancer treatment and offers targeted chemotherapies directly and selectively to cancer cells, with enhanced therapeutic efficacy. Additionally, nanotechnology elevates the chances of patient survival in comparison to traditional chemotherapies. The potential of nanoparticles includes that they may be used simultaneously for diagnosis and treatment. These exciting properties of nanoparticles have enticed researchers worldwide to unveil their use in early CRC detection and as effective treatment. This review discusses contemporary methods of CRC screening and therapies for CRC treatment, while the primary focus is on the theranostic approach of nanotechnology in CRC treatment and its prospects. In addition, this review aims to provide knowledge on the advancement of nanotechnology in CRC and as a starting point for researchers to think about new therapeutic approaches using nanotechnology.     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

The Affordable Care Act's “community first choice” option: Effect on long-term care expenditures

Objective

To empirically assess the effect of adopting Affordable Care Act's Community First Choice (CFC) option on overall state home and community-based services (HCBS) expenditures as well as distribution of HCBS expenditures across different HCBS mechanisms. We also explore the heterogeneous effect of CFC across adopting states.

Data Source

We used data from the Medicaid Long Term Services and Support (LTSS) expenditure reports prepared by Truven Analytics and Mathematica for the Centers for Medicare & Medicaid Services from 2008–2018 for all 48 states and the District of Columbia.

Study Design

An event-study difference-in-differences model was used to estimate the effect of CFC on HCBS expenditures using Medicaid LTSS expenditure reports from 2008–2018. We also employ the synthetic control method to unmask heterogeneity across CFC adopting states using data from 2008–2018.

Data Collection/Extraction Methods

Not applicable.

Principal Findings

Overall, CFC was not associated with a change in HCBS expenditures per capita or HCBS expenditures as a proportion of LTSS expenditures. However, there appears to be an increase in HCBS expenditures among states that were institutionally-oriented prior to CFC adoption. Additionally, CFC adoption was associated with an overall decrease in expenditures in alternative HCBS mechanisms (Personal Care Services State Plan Option and 1915(c) waivers), suggesting potential substitution across overlapping programs.

Conclusion

Results indicate heterogeneity across states adopting CFC. More institutionally-oriented states appear to use CFC to expand HCBS. In contrast, more HCBS-oriented states appear to employ CFC to strategically restructure their overall portfolio and processes.     

The role of payment and financing in achieving health equity

Objective

The aim was to identify healthcare payment and financing reforms to promote health equity and ways that the Agency for Healthcare Research and Quality (AHRQ) may promote those reforms.

Data Sources and Study Setting

AHRQ convened a payment and financing workgroup–the authors of this paper–as part of its Health Equity Summit held in July 2022. This workgroup drew from its collective experience with healthcare payment and financing reform, as well as feedback from participants in a session at the Health Equity Summit, to identify the evidence base and promising paths for reforms to promote health equity.

Study Design

The payment and financing workgroup developed an outline of reforms to promote health equity, presented the outline to participants in the payment and financing session of the July 2022 AHRQ Health Equity Summit, and integrated feedback from the participants.

Data Collection/Extraction Methods

This paper did not require novel data collection; the authors collected the data from the existing evidence base.

Principal Findings

The paper outlines root causes of health inequity and corresponding potential reforms in five domains: (1) the differential distribution of resources between healthcare providers serving different communities, (2) scarcity of financing for populations most in need, (3) lack of integration/accountability, (4) patient cost barriers to care, and (5) bias in provider behavior and diagnostic tools.

Conclusions

Additional research is necessary to determine whether the proposed reforms are effective in promoting health equity.