Objective: To characterize biological and technical factors which influence cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker levels, including the presence of apolipoprotein E (APOE) ε4 allele, AD diagnosis, Aβ‐binding proteins, sample processing, and preanalytical handling.Methods: CSF was collected from 140 subjects with normal cognition, mild cognitive impairment, AD, and non‐AD dementia. CSF levels of beta‐amyloid 1–42 (Aβ42), total Tau (t‐Tau), and Tau phosphorylated at threonine 181 (p‐Tau181) were analyzed following the standard and modified protocols. CSF levels of apoJ, apoE, albumin, and α‐synuclein were measured in a subgroup (n = 69), and their effects on measured AD biomarker levels were also determined in vitro using human CSF samples.Results: CSF Aβ42 levels measured using the AD Neuro‐imaging Initiative (ADNI) protocol (which we call suspended Aβ42 or susAβ) were lower than total measurable CSF Aβ42 in all groups, and on average represents 57% of the latter. Logistic regression analysis showed this proportion (% susAβ) to be directly correlated with CSF Aβ42 and apoJ levels, but inversely correlated with CSF t‐Tau levels. Finally, we showed in vitro that increasing apoE and apoJ levels directly increased % susAβ.Conclusion: CSF susAβ levels are influenced by biological and technical factors, and may represent a marker of Aβ susceptible to lipoprotein‐mediated clearance. Clinical trials should include total measurable Aβ42 and susAβ to better inform outcomes.

Objectives The US Center for Disease Control and Prevention’s National Death Index (NDI) is a gold standard for mortality data, yet matching patients to the database depends on accurate and available key identifiers. Our objective was to evaluate NDI data for future healthcare research studies with mortality outcomes. Methods We used a Kaiser Permanente Mid-Atlantic States’ Virtual Data Warehouse (KPMAS-VDW) sourced from the Social Security Administration and electronic health records on members enrolled between 1 January 2005 to 31 December 2017. We submitted data to NDI on 1 036 449 members. We compared results from the NDI best match algorithm to the KPMAS-VDW for vital status and death date. We compared probabilistic scores by sex and race and ethnicity. Results NDI returned 372 865 (36%) unique possible matches, 663 061 (64%) records not matched to the NDI database and 522 (<1%) rejected records. The NDI algorithm resulted in 38 862 records, presumed dead, with a lower percentage of women, and Asian/Pacific Islander and Hispanic people than presumed alive. There were 27 306 presumed dead members whose death dates matched exactly between the NDI results and VDW, but 1539 did not have an exact match. There were 10 017 additional deaths from NDI results that were not present in the VDW death data. Conclusions NDI data can substantially improve the overall capture of deaths. However, further quality control measures were needed to ensure the accuracy of the NDI best match algorithm.

Ovarian cancer (OVCA) patients may carry genes conferring cancer risk to biological family; however, fewer than one-quarter of patients receive genetic testing. “Traceback” cascade testing —outreach to potential probands and relatives—is a possible solution. This paper outlines a funded study (U01 CA240747-01A1) seeking to determine a Traceback program’s feasibility, acceptability, effectiveness, and costs. This is a multisite prospective observational feasibility study across three integrated health systems. Informed by the Conceptual Model for Implementation Research, we will outline, implement, and evaluate the outcomes of an OVCA Traceback program. We will use standard legal research methodology to review genetic privacy statutes; engage key stakeholders in qualitative interviews to design communication strategies; employ descriptive statistics and regression analyses to evaluate the site differences in genetic testing and the OVCA Traceback testing; and assess program outcomes at the proband, family member, provider, system, and population levels. This study aims to determine a Traceback program’s feasibility and acceptability in a real-world context. It will account for the myriad factors affecting implementation, including legal issues, organizational- and individual-level barriers and facilitators, communication issues, and program costs. Project results will inform how health care providers and systems can develop effective, practical, and sustainable Traceback programs.

Since 2020, the US Preventive Services Taskforce has recommended expanding hepatitis C virus (HCV) screening to include ages 18−79, in addition to baby boomers (born 1945−1965) and those at-risk for hepatitis C virus. This retrospective cohort analysis compared patients (18 years and above) tested for HCV through usual care versus a coordinator-supported program (HCV pathway) during 2015−2018 within Kaiser Permanente Mid-Atlantic States (KPMAS). In total, 131,176 patients were tested through the HCV pathway and 128,311 through usual care (non-standardized testing). Of those tested, 1.6% (HCV pathway) and 0.5% (usual care) had chronic HCV. Of those with chronic HCV, more patients tested within the HCV pathway completed hepatic transient elastography (82.6% HCV pathway vs. 45.6% usual care; p < 0.001) and a gastroenterology visit (72.2% HCV pathway vs. 46.5% usual care; p < 0.001), and had filled prescriptions for treatment (56.5% HCV pathway vs. 40.3% usual care; p < 0.001). The median time to complete each step was shorter for those tested through the HCV pathway (hepatic transient elastography (26 vs. 118 days), gastroenterology visit (63 vs. 131 days), and prescription fill (222 vs. 326 days)). More patients tested through a coordinator-supported, standardized testing pathway completed the necessary testing steps, in less time, compared to usual care. These findings may inform institutions seeking to create effective population-wide testing programs for HCV and other conditions.

Background: Traceback testing—identifying and offering testing to people with previous cancer diagnoses who have not received current standard genetic testing—could benefit patients and their at-risk relatives. Methods: We conducted a multisite, nonrandomized pilot implementation study of a Traceback program at three integrated United States health systems. We assessed the reach, fidelity, effectiveness, and acceptability of the program using quantitative and qualitative methods. Results: We identified 597 eligible individuals using administrative data and manual chart review. We attempted to reach everyone identified (100% fidelity). We successfully contacted 354 people, for a reach of 59% of confirmed eligible individuals. In total, 133 people completed Traceback genetic testing. Ten of these (8%) received pathogenic or likely pathogenic results;. Nine of these ten people received positive results for which cascade testing of at-risk relatives would be indicated. None of their relatives underwent cascade testing during the study period. Thirty-six received variants of uncertain significance (VUS). Traceback programs were acceptable to participants and implementers and thought to be applicable to other genetic screening conditions. The time and resources required to accurately identify Traceback-eligible individuals are likely determinants of future sustainability. Conclusions: Education about free cascade testing, reminder calls to probands, and offers to directly contact at-risk relatives did not result in cascade testing in this pilot study. However, participant and implementer discussions suggest that the potential benefits of Traceback programs and high participant acceptability are worthy of further study.

Despite national guidelines for genetic testing in newly diagnosed patients with ovarian cancer, overall uptake remains low. The Feasibility and Assessment of a Cascade Traceback Screening program (FACTS) study aims to increase overall uptake of genetic testing by implementing pilot traceback cascade screening programs at three integrated health systems. A traceback cascade screening program for ovarian cancer evaluates inherited cancer risk in individuals with a personal history of ovarian cancer and their at-risk relatives, facilitated through retrospective outreach to eligible individuals. Assessment of real-world uptake of genetic testing can help to inform acceptance and feasibility of traceback programs for broader implementation.