Outcomes Following a False-Positive Multi-Cancer Early Detection Test: Results from DETECT-A, the First Large, Prospective, Interventional MCED Study.

Guideline recommended standard of care screening is available for four cancer types; most cancer-related deaths are caused by cancers without standard of care screening. DETECT-A is the first prospective interventional trial evaluating a multi-cancer early detection (MCED) blood test (CancerSEEK) in women without a history of cancer, providing the first opportunity to assess the long-term outcomes of individuals with false-positive (FP) MCED results. This prospective analysis of DETECT-A participants with FP results evaluates the performance of an imaging-based diagnostic workflow and examines cancer risk following a FP result. This analysis included all DETECT-A participants with a positive CancerSEEK test and subsequent flourine-18 fluorodeoxyglucose positron emission tomography-IV contrast-enhanced computed tomography (18-F-FDG PET-CT) imaging and clinical workup indicating no evidence of cancer within 1 year of enrollment (n = 98). Medical records, study interactions, and study surveys were used to assess cancer incidence, treatments, and clinical outcomes through August 2023. Ninety-five of 98 participants with a FP result remained cancer-free with a median follow-up of 3.6 years (IQR: 2.5-4.1) from determination of FP status. Three incident cancers were observed over the follow-up period. One bilateral stage IIIC ovarian cancer was diagnosed 1.9 years after determination of FP status; two stage I breast cancers were diagnosed 0.1 and 1.6 years from determination of FP status. The annual incidence rate of cancer during follow-up from FP determination was 1.0% (95% confidence interval, 0.2%-2.8%). Participants with a positive CancerSEEK test who underwent 18-F-FDG PET-CT and clinical workup without cancer findings had low risk for cancer over the following several years. Prevention Relevance: This study provides multiyear clinical outcomes data following a false-positive multi-cancer early detection test for individuals participating in a prospective interventional trial. It provides a preliminary performance assessment of an imaging-based diagnostic workflow following a false-positive multi-cancer early detection test.

Outcomes following a false positive multi-cancer early detection (MCED) test: Results from DETECT-A, the first large, prospective, interventional MCED study.

Guideline recommended standard of care (SoC) screening is available for four cancer types; most cancer-related deaths are caused by cancers without SoC screening. DETECT-A is the first prospective interventional trial evaluating an MCED blood test (CancerSEEK) in women without a history of cancer, providing the first opportunity to assess the long-term outcomes of individuals with false positive (FP) MCED results. This prospective analysis of DETECT-A participants with FP results evaluates the performance of an imaging-based diagnostic workflow and examines cancer risk following a FP result. This analysis included all DETECT-A participants with a positive CancerSEEK test and subsequent flourine-18 fluorodeoxyglucose positron emission tomography-IV contrast enhanced computed tomography (18-F-FDG PET-CT) imaging and clinical workup indicating no evidence of cancer within one year of enrollment (n=98). Medical records, study interactions, and study surveys were used to assess cancer incidence, treatments, and clinical outcomes through August 2023. Ninety-five of 98 participants with a FP result remained cancer-free with a median follow-up of 3.6 years (IQR: 2.5-4.1) from determination of FP status. Three incident cancers were observed over the follow-up period. One bilateral stage IIIC ovarian cancer was diagnosed 1.9 years after determination of FP status; two stage I breast cancers were diagnosed 0.1 and 1.6 years from determination of FP status. The annual incidence rate of cancer during follow-up from FP determination was 1.0% (95% CI: 0.2%-2.8%). Participants with a positive CancerSEEK test who underwent 18-F-FDG PET-CT and clinical workup without cancer findings had low risk for cancer over the following several years.

Multi-year clinical outcomes of cancers diagnosed following detection by a blood-based multi-cancer early detection (MCED) test.

In the U.S., <20% of cancers are diagnosed by standard-of-care (SoC) screening. Multi-cancer early detection (MCED) tests offer the opportunity to expand cancer screening. Understanding the characteristics and clinical outcomes of MCED-detected cancers is critical to clarifying MCED tests' potential impact. DETECT-A is the first prospective interventional trial of an MCED blood test (CancerSEEK). CancerSEEK, coupled with diagnostic PET-CT, identified cancers including those not detected by SoC screening, the majority of which were localized or regional. We report multi-year outcomes in patients with cancers diagnosed following a positive CancerSEEK test. Nine cancer types were diagnosed in 26 participants whose cancers were first detected by CancerSEEK. Information on cancer diagnoses, treatments, and clinical outcomes was extracted from medical records through November 2022. Data collection occurred a median of 4.4 years (IQR: 4.1-4.6) following study enrollment. Thirteen of 26 (50%) participants were alive and cancer-free [ovarian (4), thyroid (1), uterine (2), breast (1), colorectal (2), and lung (3)]; 7/13 (54%) had cancers without recommended SoC screening modalities. All 8 treated stage I or II participants (8/8, 100%) and 12/14 (86%) surgically-treated participants were alive and cancer-free. Eligibility for surgical treatment was associated with favorable multi-year outcomes (p = 0.0002). Half of participants with MCED-detected cancers were alive and cancer-free after 4.4 years median follow-up. Most were diagnosed with early-stage cancers and were treated surgically. These results suggest that early cancer detection by CancerSEEK may have facilitated curative-intent treatments and associated positive clinical outcomes in some DETECT-A participants.

Real-time evaluation and adaptation to facilitate rapid recruitment in a large, prospective cohort study.

BACKGROUND: Recruiting large cohorts efficiently can speed the translation of findings into care across a range of scientific disciplines and medical specialties. Recruitment can be hampered by factors such as financial barriers, logistical concerns, and lack of resources for patients and clinicians. These and other challenges can lead to underrepresentation in groups such as rural residents and racial and ethnic minorities. Here we discuss the implementation of various recruitment strategies for enrolling participants into a large, prospective cohort study, assessing the need for adaptations and making them in real-time, while maintaining high adherence to the protocol and high participant satisfaction. METHODS: While conducting a large, prospective trial of a multi-cancer early detection blood test at Geisinger, an integrated health system in central Pennsylvania, we monitored recruitment progress, adherence to the protocol, and participants' satisfaction. Tracking mechanisms such as paper records, electronic health records, research databases, dashboards, and electronic files were utilized to measure each outcome. We then reviewed study procedures and timelines to list the implementation strategies that were used to address barriers to recruitment, protocol adherence and participant satisfaction. RESULTS: Adaptations to methods that contributed to achieving the enrollment goal included offering multiple recruitment options, adopting group consenting, improving visit convenience, increasing the use of electronic capture and the tracking of data and source documents, staffing optimization via leveraging resources external to the study team when appropriate, and integrating the disclosure of study results into routine clinical care without adding unfunded work for clinicians. We maintained high protocol adherence and positive participant experience as exhibited by a very low rate of protocol deviations and participant complaints. CONCLUSION: Recruiting rapidly for large studies - and thereby facilitating clinical translation - requires a nimble, creative approach that marshals available resources and changes course according to data. Planning a rigorous assessment of a study's implementation outcomes prior to study recruitment can further ground study adaptations and facilitate translation into practice. This can be accomplished by proactively and continuously assessing and revising implementation strategies.

Characterizing primary care for patients with major depressive disorder using electronic health records of a US-based healthcare provider.

BACKGROUND: Major depressive disorder (MDD) is predominantly managed in primary care. However, primary care providers (PCPs) may not consistently follow evidence-based treatment algorithms, leading to variable patient management that can impact outcomes. METHODS: We retrospectively analyzed adult patients with MDD seen at Geisinger, an integrated health system. Utilizing electronic health record (EHR) data, we classified patients as having MDD based on International Classification of Disease (ICD)-9/10 codes or a Patient Health Questionnaire (PHQ)-9 score ≥5. Outcomes assessed included time to first visit with a PCP or behavioral health specialist following diagnosis, antidepressant medication switching, persistence, healthcare resource utilization (HRU), and treatment costs. RESULTS: Among the 38,321 patients with MDD managed in primary care in this study, significant delays between diagnosis with antidepressant prescribing and follow-up PCP visits were observed. There was also considerable variation in care following diagnosis. Overall, 34.9% of patients with an ICD-9/10 diagnosis of MDD and 41.3% with a PHQ-9 score ≥15 switched antidepressants. An ICD-9/10 diagnosis, but not moderately severe to severe depression, was associated with higher costs and HRU. More than 75% of patients with MDD discontinued antidepressant medication within 6 months. LIMITATIONS: The study population was comparable with other real-world studies of MDD, but study limitations include its retrospective nature and reliance on the accuracy of EHRs. CONCLUSIONS: Management of patients with MDD in a primary care setting is variable. Addressing these gaps will have important implications for ensuring optimal patient management, which may reduce HRU and treatment medication costs, and improve treatment persistence.

Does Preoperative Platelet Function Predict Bleeding in Patients Undergoing Off Pump Coronary Artery Bypass Surgery?

OBJECTIVE: We sought to examine the relationship between preoperative platelet function and perioperative bleeding in patients undergoing CABG. BACKGROUND: There are many ways to measure platelet aggregability. Little is known about their correlations with one another, or with bleeding. METHODS: We prospectively studied 50 patients undergoing a first isolated off-pump CABG. Thirty-four were exposed to a thienopyridine prior to surgery; 16 were not. Preoperative platelet function was measured by VerifyNow®, TEG®, AggreGuide™, Plateletworks®, vasodilator-stimulated phosphoprotein (VASP) phosphorylation, and light transmission aggregometry. Bleeding was assessed 2 ways: drop from pre- to nadir postoperative hematocrit, and chest tube drainage. Correlation coefficients were calculated using Spearman's rank-order correlation. RESULTS: Mean age was 62 years. Patient characteristics and surgical details were similar between the thienopyridine-exposed and non-exposed patients. The correlation coefficients between the 4 point-of-care platelet function measurements and hematocrit change ranged from -0.2274 to 0.2882. Only Plateletworks® correlated with drop in hematocrit (r = 0.2882, P = 0.0470). The correlation coefficients between each of the 4 point-of-care platelet function tests and the chest tube drainage were also poor, ranging from -0.3073 to 0.2272. Both AggreGuide™ (r = -0.3073, P = 0.0317) and VASP (r = -0.3187, P = 0.0272) were weakly but significantly correlated with chest tube drainage. The correlation among the 4 point-of-care platelet function measurements was poor, with coefficients ranging from -0.2504 to 0.1968. CONCLUSIONS: We observed little correlation among 4 platelet function tests, and between those assays and perioperative bleeding defined 2 different ways. Whether any of these assays should be used to guide decision making in individual patients is unclear.