Gaustad Hospital

The modified Atkins diet is increasingly used as an adjunctive therapy for drug-resistant epilepsy. Recent evidence suggests that such dietary interventions may affect the pharmacokinetics of antiseizure medications and induce DNA methylation changes. However, it remains unclear whether epigenetic regulation of drug-metabolizing enzymes contributes to variability in medication serum levels. We analyzed 58 adults with drug-resistant epilepsy treated with a modified Atkins diet for 12 weeks. DNA methylation was profiled in peripheral blood before diet initiation (baseline) and after 4 weeks and 12 weeks using a genome-wide array. A total of 131 cytosine-phosphate-guanine (CpG) sites mapped to 13 candidate genes involved in antiseizure medication metabolism were assessed. One CpG in the CES1 gene showed significant methylation changes from baseline to 4 weeks, 12 weeks, and across all timepoints (FDR = 0.0018), indicating consistent longitudinal effects. Repeated measures correlation analyses were used to evaluate within-individual associations between DNA methylation and antiseizure medication serum concentrations. Two CpG–drug associations showed strong positive intra-individual correlations: CYP3A5 methylation was significantly associated with carbamazepine serum levels (repeated measures correlation coefficient = 0.81, FDR = 0.023), whereas CYP3A4 methylation showed a similarly strong but borderline association with topiramate (correlation coefficient = 0.76, FDR = 0.051). This study finds that a modified Atkins diet may be associated with DNA methylation variation at genes involved in drug metabolism. Furthermore, DNA methylation levels were strongly associated with individual serum concentrations of certain antiseizure medications. These findings are consistent with the concept of a diet–epigenome–drug metabolism axis and warrant further investigation in larger studies to assess clinical implications for personalized dietary and pharmacological management in epilepsy.

BackgroundDistinguishing postoperative fibrosis from isolated local recurrence (ILR) after resection of pancreatic ductal adenocarcinoma (PDAC) is challenging. A prognostic model that helps to identify patients at risk of ILR can assist clinicians when evaluating patients’ postoperative imaging. This nationwide study aimed to develop a clinically applicable prognostic model for ILR after PDAC resection.Patients and MethodsAn observational cohort study was performed, including all patients who underwent PDAC resection in the Netherlands (2014–2019; NCT04605237). On the basis of recurrence location (ILR, systemic, or both), multivariable cause-specific Cox-proportional hazard analysis was conducted to identify predictors for ILR and presented as hazard ratios (HRs) with 95% confidence intervals (CIs). A predictive model was developed using Akaike’s Information Criterion, and bootstrapped discrimination and calibration indices were assessed.ResultsAmong 1194/1693 patients (71%) with recurrence, 252 patients (21%) developed ILR. Independent predictors for ILR were resectability status (borderline versus resectable, HR 1.42; 95% CI 1.03–1.96; P = 0.03, and locally advanced versus resectable, HR 1.11; 95% CI 0.68–1.82; P = 0.66), tumor location (head versus body/tail, HR 1.50; 95% CI 1.00–2.25; P = 0.05), vascular resection (HR 1.86; 95% CI 1.41–2.45; P < 0.001), perineural invasion (HR 1.47; 95% CI 1.01–2.13; P = 0.02), number of positive lymph nodes (HR 1.04; 95% CI 1.01–1.08; P = 0.02), and resection margin status (R1 < 1 mm versus R0 ≥ 1 mm, HR 1.64; 95% CI 1.25–2.14; P < 0.001). Moderate performance (concordance index 0.66) with adequate calibration (slope 0.99) was achieved.ConclusionsThis nationwide study identified factors predictive of ILR after PDAC resection. Our prognostic model, available through www.pancreascalculator.com, can be utilized to identify patients with a higher a priori risk of developing ILR, providing important information in patient evaluation and prognostication.

BackgroundUnnecessary D2-gastrectomy and associated costs can be prevented after detecting non-curable gastric cancer, but impact of staging on treatment costs is unclear. This study determined the cost impact of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18FFDG-PET/CT) and staging laparoscopy (SL) in gastric cancer staging.Materials and MethodsIn this cost analysis, four staging strategies were modeled in a decision tree: (1) 18FFDG-PET/CT first, then SL, (2) SL only, (3) 18FFDG-PET/CT only, and (4) neither SL nor 18FFDG-PET/CT. Costs were assessed on the basis of the prospective PLASTIC-study, which evaluated adding 18FFDG-PET/CT and SL to staging advanced gastric cancer (cT3–4 and/or cN+) in 18 Dutch hospitals. The Dutch Healthcare Authority provided 18FFDG-PET/CT unit costs. SL unit costs were calculated bottom-up. Gastrectomy-associated costs were collected with hospital claim data until 30 days postoperatively. Uncertainty was assessed in a probabilistic sensitivity analysis (1000 iterations).Results18FFDG-PET/CT costs were €1104 including biopsy/cytology. Bottom-up calculations totaled €1537 per SL. D2-gastrectomy costs were €19,308. Total costs per patient were €18,137 for strategy 1, €17,079 for strategy 2, and €19,805 for strategy 3. If all patients undergo gastrectomy, total costs were €18,959 per patient (strategy 4). Performing SL only reduced costs by €1880 per patient. Adding 18FFDG-PET/CT to SL increased costs by €1058 per patient; IQR €870–1253 in the sensitivity analysis.ConclusionsFor advanced gastric cancer, performing SL resulted in substantial cost savings by reducing unnecessary gastrectomies. In contrast, routine 18FFDG-PET/CT increased costs without substantially reducing unnecessary gastrectomies, and is not recommended due to limited impact with major costs.Trial registration: NCT03208621. This trial was registered prospectively on 30-06-2017.

Objective Methotrexate (MTX) is the cornerstone in the treatment of rheumatoid arthritis (RA) patients. However, adherence to MTX therapy is not optimal, and instruments to assess medication non-adherence are warranted. To date there is no consensus on the best method to determine adherence to MTX. The aim of this study was to assess the correlation between adherence assessed with a Medication Event Monitoring System (MEMS) versus pill count, MTX-polyglutamate (PG) concentration and Compliance-Questionnaire-Rheumatology (CQR) in patients with established RA. Second, the correlations between these methods and the Disease Activity Scores of 28 joints (DAS28) were examined. Methods Adult RA patients currently treated with MTX were included. Multivariable linear and logistic regression were used, with adherence assessed with MEMS as dependent variable versus pill count, MTX-PG concentrations, CQR as independent variables, and DAS28 versus each of the four adherence measurements. Covariates were included, such as comedication, age and use of corticosteroids. Results 190 consecutive RA patients were included. Pill count was correlated with adherence assessed with MEMS (linear regression, β = .690, p = &lt;.001), whereas CQR and MTX-PGs were not. Logistic regression confirmed the correlation between dichotomized adherence and pill count only (β = 5.64, p= &lt;.001). No other correlations were found, neither for all adherence outcomes and DAS28. Conclusion Measuring adherence with MEMS is correlated with pill count, whereas other methods were not correlated with MEMS, nor with DAS28. Pill count can be used to estimate adherence to MTX therapy, in case MEMS is not achievable.

BackgroundAlthough the treatment for breast cancer is highly personalized, posttreatment surveillance remains one-size-fits-all: annual imaging and physical examination for at least five years after treatment. The INFLUENCE nomogram is a prognostic model for estimating the 5-year risk for locoregional recurrences and second primary tumors after breast cancer. The use of personalized outcome data (such as risks for recurrences) can enrich the process of shared decision-making (SDM) for personalized surveillance after breast cancer.ObjectiveThis study aimed to develop a patient decision aid (PtDA), integrating personalized risk calculations on risks for recurrences, to support SDM for personalized surveillance after curative treatment for invasive breast cancer.MethodsFor the development of the PtDA, the International Patient Decision Aids Standards development process was combined with a mixed methods design inspired by the development process of previously developed PtDAs. In the development, 8 steps were distinguished: establishing a multidisciplinary steering group; definition of the end users, scope, and purpose of the PtDA; assessment of the decisional needs of end users; defining requirements for the PtDA; determining the format and implementation strategy for the PtDA; prototyping; alpha testing; and beta testing. The composed steering group convened during regular working-group sessions throughout the development process.ResultsThe “Breast Cancer Surveillance Decision Aid” consists of 3 components that support the SDM process: a handout sheet on which personalized risks for recurrences, calculated using the INFLUENCE-nomogram, can be visualized and which contains an explanation about the decision for surveillance and a login code for a web-based deliberation tool; a web-based deliberation tool, including a patient-reported outcome measure on fear of cancer recurrence; and a summary sheet summarizing patient preferences and considerations. The PtDA was assessed as usable and acceptable during alpha testing. Beta testing is currently ongoing.ConclusionsWe developed an acceptable and usable PtDA that integrates personalized risk calculations for the risk for recurrences to support SDM for surveillance after breast cancer. The implementation and effects of the use of the “Breast Cancer Surveillance Decision Aid” are being investigated in a clinical trial.

Rheumatoid Arthritis (RA) is a chronic disease that impacts patients’ quality of life. Sophisticated organization of care delivery drives quality improvement. Therefore, the study objective was establishing a validated process map of the care cycle for RA patients. Hence, increasing transparency and optimizing care delivery and identifying areas of improvement. To map the RA care cycle, the care delivery value chain (CDVC) approach was used as framework to document activities and resources systematically. A mixed method study was conducted where quantitative data on activities were collected from health records and unstructured interviews with medical staff were held. Consequently, the process map was separately validated in a consensus meeting with a delegation of the medical staff and patient advisory board. At the start of the care cycle, the focus is predominantly on defining the treat-to-target strategy and examining disease activity. Towards the monitoring phase, tapering medication and managing the disease through patient-reported outcome measures are becoming increasingly important. Although patient’s functioning, quality of care and patient’s evaluation of received care are monitored, reflection of CDVC and engaging patients in the evaluation process resulted in improvement actions on outcome and process level. Mapping the RA care cycle following a systematic approach, provides insight and transparency in delivered activities, involved resources and the engagement of patients and caregivers at multiple levels, contributing to a system facilitating value-based care delivery. The CDVC framework and applied methodology is recommended in other conditions. Future research will focus at assigning outcomes and costs to activities and evaluating interventions to explore patient value.