Rising Economic Burden of Renal Cell Carcinoma among Elderly Patients in the USA: Part II-An Updated Analysis of SEER-Medicare Data

Artificial intelligence support in MR imaging of incidental renal masses: an early health technology assessment

OBJECTIVE

This study analyzes the potential cost-effectiveness of integrating an artificial intelligence (AI)-assisted system into the differentiation of incidental renal lesions as benign or malignant on MR images during follow-up.

MATERIALS AND METHODS

For estimation of quality-adjusted life years (QALYs) and lifetime costs, a decision model was created, including the MRI strategy and MRI + AI strategy. Model input parameters were derived from recent literature. Willingness to pay (WTP) was set to $100,000/QALY. Costs of $0 for the AI were assumed in the base-case scenario. Model uncertainty and costs of the AI system were assessed using deterministic and probabilistic sensitivity analysis.

RESULTS

Average total costs were at $8054 for the MRI strategy and $7939 for additional use of an AI-based algorithm. The model yielded a cumulative effectiveness of 8.76 QALYs for the MRI strategy and of 8.77 for the MRI + AI strategy. The economically dominant strategy was MRI + AI. Deterministic and probabilistic sensitivity analysis showed high robustness of the model with the incremental cost-effectiveness ratio (ICER), which represents the incremental cost associated with one additional QALY gained, remaining below the WTP for variation of the input parameters. If increasing costs for the algorithm, the ICER of $0/QALY was exceeded at $115, and the defined WTP was exceeded at $667 for the use of the AI.

CONCLUSIONS

This analysis, rooted in assumptions, suggests that the additional use of an AI-based algorithm may be a potentially cost-effective alternative in the differentiation of incidental renal lesions using MRI and needs to be confirmed in the future.

CLINICAL RELEVANCE STATEMENT

These results hint at AI's the potential impact on diagnosing renal masses. While the current study urges careful interpretation, ongoing research is essential to confirm and seamlessly integrate AI into clinical practice, ensuring its efficacy in routine diagnostics.

KEY POINTS

• This is a model-based study using data from literature where AI has been applied in the diagnostic workup of incidental renal lesions. • MRI + AI has the potential to be a cost-effective alternative in the differentiation of incidental renal lesions. • The additional use of AI can reduce costs in the diagnostic workup of incidental renal lesions.

Cost-effectiveness of minimally invasive partial nephrectomy and percutaneous cryoablation for cT1a renal cell carcinoma

BACKGROUND

There is growing evidence that partial nephrectomy (PN) and percutaneous cryoablation (PCA) yield comparable outcomes for patients with cT1a renal cell carcinoma (RCC), although the cost-effectiveness of both treatments still needs to be assessed.

PURPOSE

To perform a cost-effectiveness analysis of PN and PCA for patients with cT1a RCC.

MATERIALS AND METHODS

A decision analysis was created over a 5-year span from a healthcare payer's perspective computing expected costs and outcomes of PN and PCA in terms of quality-adjusted life-years (QALYs) and incremental cost-effectiveness (ICER). After each treatment, the following states were modelled using data from the recent literature: procedural complications, no evidence of disease (NED), local recurrence, metastases, and death from RCC- or non-RCC-related causes. Probabilistic and deterministic sensitivity analyses were performed.

RESULTS

PCA and PN yielded health benefits of 3.68 QALY and 3.67 QALY. Overall expected costs were $20,491 and $26,478 for PCA and PN. On probabilistic sensitivity analysis, PCA was more cost-effective than PN in 84.78% of Monte Carlo simulations. PCA was more cost-effective until its complication risk was at least 38% higher than PN. PCA was more cost-effective than PN when (i) PCAs annual local recurrence risk was < 3.5% higher than that of PN in absolute values; (ii) PCAs annual metastatic risk was < 1.0% higher than that of PN; or (iii) PCAs annual cancer-specific mortality risk < 0.65% higher than that of PN. PCA remained cost-effective until its procedural cost is above $13,875.

CONCLUSION

PCA appears to be more cost-effective than PN for the treatment of cT1a RCC, although the currently available evidence is of limited quality. PCA may be the better treatment strategy in the majority of scenarios varying procedural complications, recurrence, metastatic risk, and RCC-mortality in clinically plausible ranges.

KEY POINTS

• For patients with cT1a RCCs, PCA yields a comparable health benefit at lower costs compared to PN, making PCA the dominant and therefore more cost-effective treatment strategy over PN. • PCA was more cost-effective than PN when (i) PCAs annual local recurrence risk was < 3.5% higher than PN in absolute values; (ii) PCAs annual metastatic risk was < 1.0% higher than PN; or (iii) PCAs annual cancer-specific mortality risk < 0.65% higher than PN. • PCA is more cost-effective than PN for the treatment of cT1a RCC, and it remained so in the majority of scenarios varying procedural complications, recurrence, metastatic risk, and RCC mortality.

Leveraging Systematic Reviews to Explore Disease Burden and Costs of Per- and Polyfluoroalkyl Substance Exposures in the United States

Accelerating evidence confirms the contribution of per- and polyfluoroalkyl substances (PFAS) to disease burden and disability across the lifespan. Given that policy makers raise the high cost of remediation and of substituting PFAS with safer alternatives in consumer products as barriers to confronting adverse health outcomes associated with PFAS exposure, it is important to document the costs of inaction even in the presence of uncertainty. We therefore quantified disease burdens and related economic costs due to legacy PFAS exposures in the US in 2018. We leveraged systematic reviews and used meta-analytic inputs whenever possible, identified previously published exposure-response relationships, and calculated PFOA- and PFOS-attributable increases in 13 conditions. These increments were then applied to census data to determine total annual PFOA- and PFOS-attributable cases of disease, from which we calculated economic costs due to medical care and lost productivity using previously published cost-of-illness data. We identified PFAS-attributable disease costs in the US of $5.52 billion across five primary disease endpoints shown to be associated with PFAS exposure in meta-analyses. This estimate represented the lower bound, with sensitivity analyses revealing as much as $62.6 billion in overall costs. While further work is needed to assess probability of causation and establish with greater certainty effects of the broader category of PFAS, the results confirm further that public health and policy interventions are still necessary to reduce exposure to PFOA and PFOS and their endocrine-disrupting effects. This study demonstrates the large potential economic implications of regulatory inaction.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12403-022-00496-y.

Development and Validation of a Predictive Model to Evaluate the Risk of Bone Metastasis in Kidney Cancer

Background

Bone is a common target of metastasis in kidney cancer, and accurately predicting the risk of bone metastases (BMs) facilitates risk stratification and precision medicine in kidney cancer.

Methods

Patients diagnosed with kidney cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database to comprise the training group from 2010 to 2017, and the validation group was drawn from our academic medical center. Univariate and multivariate logistic regression analyses explored the statistical relationships between the included variables and BM. Statistically significant risk factors were applied to develop a nomogram. Calibration plots, receiver operating characteristic (ROC) curves, probability density functions (PDF), and clinical utility curves (CUC) were used to verify the predictive performance. Kaplan-Meier (KM) curves demonstrated survival differences between two subgroups of kidney cancer with and without BMs. A convenient web calculator was provided for users via “shiny” package.

Results

A total of 43,503 patients were recruited in this study, of which 42,650 were training group cases and 853 validation group cases. The variables included in the nomogram were sex, pathological grade, T-stage, N-stage, sequence number, brain metastases, liver metastasis, pulmonary metastasis, histological type, primary site, and laterality. The calibration plots confirmed good agreement between the prediction model and the actual results. The area under the curve (AUC) values in the training and validation groups were 0.952 (95% CI, 0.950–0.954) and 0.836 (95% CI, 0.809–0.860), respectively. Based on CUC, we recommend a threshold probability of 5% to guide the diagnosis of BMs.

Conclusions

The comprehensive predictive tool consisting of nomogram and web calculator contributes to risk stratification which helped clinicians identify high-risk cases and provide personalized treatment options.

Provider- and patient-level predictors of oral anticancer agent initiation and adherence in patients with metastatic renal cell carcinoma

Background

Improving oral anticancer agent (OAA) initiation and adherence is the important quality‐of‐care issues, particularly since one fourth of anticancer agents being developed will be administered orally. Our objective was to identify provider‐ and patient‐level characteristics associated with OAA initiation and adherence among individuals with metastatic renal cell carcinoma (mRCC).

Methods

We used state cancer registry data linked to multi‐payer claims data to identify patients with mRCC diagnosed in 2004–2015. Provider data were obtained from North Carolina Health Professions Data System and the National Plan & Provider Enumeration System. We estimated risk ratios (RRs) and corresponding 95% confidence limits (CLs) using modified Poisson regression to evaluate factors associated with OAA initiation and adherence.

Results

Among the 207 (out of 687) patients who initiated an OAA following mRCC diagnosis and survived 90 days, median proportion of days covered was 0.91. Patients with a modal provider specializing in hematology/medical oncology were much more likely to initiate OAAs than those seen by other specialties. Additionally, patients with a female provider were more likely to initiate OAAs than those with a male provider. Compared to patients treated by providers practicing in both urban and rural areas, patients with providers practicing solely in urban areas were more likely to initiate OAAs, after controlling for patient‐level factors (RR = 1.37; 95% CL: 1.09–1.73). Medicare patients were less likely to be adherent than those with private insurance (RR = 0.61; 95% CL: 0.42–0.87).

Conclusions

Our results suggest that provider‐ and patient‐level factors influence OAA initiation in patients with mRCC but only insurance type was associated with adherence.

Changes in prescribing habits for the treatment of metastatic renal clear cell carcinoma (mRCC) in Australia

The availability of efficacious systemic therapies for metastatic clear cell renal cell carcinoma has heralded improved survival for Australians. The Pharmaceutical Benefits Schedule registry was interrogated to assess nation-wide prescribing patterns. Sunitinib remained the most commonly prescribed agent. Prescribing rates were significantly lower in Northern Territory than in other states, raising questions of disparities in access to care.

Characterizing online crowdfunding campaigns for patients with kidney cancer

Background

Cancer patients incur high care costs; however, there is a paucity of literature characterizing unmet financial obligations for patients with urologic cancers. Kidney cancer patients are particularly burdened by costs associated with novel systemic treatments. This study aimed to ascertain the characteristics of GoFundMe® crowdfunding campaigns for patients with kidney cancer, in order to better understand the financial needs of this population.

Methods

We performed a cross‐sectional, quantitative, and qualitative analysis of all kidney cancer GoFundMe® campaigns since 2010. Fundraising metrics such as goal funds and amount raised, were extracted. Eight independent investigators collected patient, disease and campaign‐level variables from campaign stories (κ = 0.72). In addition, we performed a content analysis of campaign narratives spotlighting the primary appeal of the patient's life story.

Results

A total of 486 GoFundMe® kidney cancer campaigns were reviewed. The median goal funds were 10,000USD [IQR = 5000, 20,000] and the median amount raised was 1450USD [IQR = 578, 4050]. Most campaigns were for adult males (53%) and 62% of adults had children. A minority were for pediatric patients (17%). Thirty‐seven percent of adult patients were primary wage earners and 43% reported losing their job or substantially reducing hours due to illness. Twenty‐nine percent reported no insurance or insufficient coverage. Campaigns most frequently sought funds for medical bills (60%), nonmedical bills (27%), and medical travel (23%). Qualitative campaign narratives mostly emphasized patients’ hardship (46.3%) or high moral character (35.2%). Only 8% of campaigns achieved their target funds.

Conclusions

Despite fundraising efforts, patients with kidney cancer face persistent financial barriers, incurring both medical and nonmedical cost burdens. This may be compounded by limited or no insurance. Cancer care providers should be aware of financial constraints placed on kidney cancer patients, and consider how these may impact treatment regimens.

Low REST Expression Indicates a Biomarker of Poor Prognosis in Patients with Renal Cell Carcinoma

It was initially found that neural-restrictive silencer factor/repressor 1-silencing transcription factor (REST) is a transcriptional repressor of neuronal genes in nonneuronal cells. However, it is reported to be abundantly expressed in various types of aggressive cancer cells. In this study, we evaluated the expression patterns of REST in renal cell carcinoma and found that its expression is lower in tumor tissues compared to normal tissues. The chi-square test showed that the low REST expression was closely related to patients' clinicopathologic parameters, including the pathologic stage and survival status. ROC curve showed that REST had excellent clinical diagnostic prospect. In addition, patients with low REST expression had poor over survival (OS) and relapse-free survival (RFS). Univariate and multivariate Cox regression analysis confirmed that the low REST expression was an independent predictor of poor prognosis in renal cell carcinoma. Gene set enrichment analysis identified P53 pathway, reactive oxygen species pathway, glycolysis, DNA repair, cholesterol homeostasis, and MYC targets V2 enriched with low REST expression phenotype. These results suggested that REST may be a novel biomarker for the diagnosis and prognosis of renal cell carcinoma in clinical applications.

Statistical modeling of longitudinal medical cost trajectory: renal cell cancer care cost analyses

Estimating the current cost of cancer care is important to health policy makers. An indispensable step in cost projection is to estimate cost trajectories from an incident cohort of cancer patients using longitudinal medical cost data, accounting for terminal events such as death, and right censoring due to loss of follow-up. Since the cost of cancer care and survival are correlated, a scientifically meaningful quantity for inference in this context is the mean cost trajectory conditional on survival. We propose a two-stage semiparametric approach to estimate the longitudinal cost trajectories from a joint model of longitudinal medical costs and survival. The longitudinal cost trajectories corresponding to various survival times form a bivariate surface in a triangular area. The cost trajectories are estimated using the tensor products of discretized measurement time and survival, as well as effective ridge penalties for data in 2D arrays. The proposed approach balances the practical considerations of model flexibility, statistical efficiency, and computational tractability. We used the proposed method to estimate the cost trajectories of renal cell cancer patients using the Surveillance, Epidemiology, and End Results-Medicare linked database.