Cancer treatments are often more successful when the disease is detected early. We evaluated the feasibility and safety of multicancer blood testing coupled with positron emission tomography–computed tomography (PET-CT) imaging to detect cancer in a prospective, interventional study of 10,006 women not previously known to have cancer. Positive blood tests were independently confirmed by a diagnostic PET-CT, which also localized the cancer. Twenty-six cancers were detected by blood testing. Of these, 15 underwent PET-CT imaging and nine (60%) were surgically excised. Twenty-four additional cancers were detected by standard-of-care screening and 46 by neither approach. One percent of participants underwent PET-CT imaging based on false-positive blood tests, and 0.22% underwent a futile invasive diagnostic procedure. These data demonstrate that multicancer blood testing combined with PET-CT can be safely incorporated into routine clinical care, in some cases leading to surgery with intent to cure.

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BackgroundThough warfarin has historically been the primary oral anticoagulant for stroke prevention in newly diagnosed atrial fibrillation (AF), several new direct oral anticoagulants may be preferred when anticoagulation control with warfarin is expected to be poor. This study developed a prediction model for time in therapeutic range (TTR) among newly diagnosed AF patients on newly initiated warfarin as a tool to assist decision making between warfarin and direct oral anticoagulants.Methods and ResultsThis electronic medical record–based, retrospective study included newly diagnosed, nonvalvular AF patients with no recent warfarin exposure receiving primary care services through a large healthcare system in rural Pennsylvania. TTR was estimated as the percentage of time international normalized ratio measurements were between 2.0 and 3.0 during the first year following warfarin initiation. Candidate predictors of TTR were chosen from data elements collected during usual clinical care. A TTR prediction model was developed and temporally validated and its predictive performance was compared with the SAMe‐TT 2R2 score (sex, age, medical history, treatment, tobacco, race) using R 2 and c‐statistics. A total of 7877 newly diagnosed AF patients met study inclusion criteria. Median (interquartile range) TTR within the first year of starting warfarin was 51% (32, 67). Of 85 candidate predictors evaluated, 15 were included in the final validated model with an R 2 of 15.4%. The proposed model showed better predictive performance than the SAMe‐TT 2R2 score (R 2=3.0%).ConclusionsThe proposed prediction model may assist decision making on the proper mode of oral anticoagulant among newly diagnosed AF patients. However, predicting TTR on warfarin remains challenging.

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Objectives Recruiting large, diverse cohorts efficiently can speed the translation of findings into care across a range of scientific disciplines and medical specialties. Yet, efficient recruitment can be hampered by factors such as financial barriers, logistical concerns, and lack of resources for patients and clinicians. Here we use a case study of a large, prospective trial of a multicancer early detection test to describe how the study team tracked enrollment, protocol fidelity, and participant experience and iteratively adapted procedures. Methods While conducting a large, prospective trial of a multicancer early detection blood test at Geisinger, an integrated health system in central Pennsylvania, we monitored recruitment progress, fidelity to protocol procedures, 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 fidelity and participant satisfaction. Results We enrolled 10,006 women ages 65 to 75 over 22 months. Adaptations to recruitment and enrollment methods that contributed to achieving the enrollment goal included adopting group consenting, improving visit convenience, increasing electronic capture and 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 physicians. We maintained high protocol fidelity and positive participant experience as exhibited by a very low protocol deviation rate and a low number of 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 studys 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.