It is not clear if patients are less adherent to low molecular weight heparin (LMWH) compared to direct oral anticoagulants (DOACs) for cancer‐associated thrombosis (CAT). We evaluated medication adherence among two propensity‐matched groups of patients with CAT by comparing the proportion of days covered (PDC). Median treatment persistence on DOACs was more than 80 days longer than LMWH. Medication adherence was high (~95%) and was similar with LMWH compared to DOACs. Abstract BackgroundLow molecular weight heparin (LMWH) and direct oral anticoagulants (DOACs) are used to treat cancer‐associated thrombosis (CAT). It is not clear if patients are less adherent to LMWH compared to DOACs. ObjectivesTo compare medication persistence and adherence between LMWH and DOACs. Patients/MethodsWe analyzed Optum's de‐identified Clinformatics® Data Mart Database of privately insured adults with cancer diagnosed between January 2009 and October 2015 who were undergoing chemotherapy, immunotherapy, targeted or hormonal therapies; developed CAT; and were treated with an outpatient anticoagulant. The proportion of days covered (PDC) was calculated from the date of anticoagulant prescription until the anticoagulant was switched, stopped, or the study end. Medication adherence was defined as PDC ≥ 80%, ≥95%, and by comparing the mean PDC. ResultsTwo propensity‐matched groups of 1128 patients were identified. Patient persistence was higher with DOACs compared to LMWH (median 116 days versus 34 days). With adherence defined as PDC ≥ 80%, we found no significant difference (95.6% versus 94.6% adherence with DOACs versus LMWH, P = .33). The mean difference of PDC between the two groups was also similar. With medication adherence defined as PDC ≥ 95%, adherence was evident in 73% of DOAC users and 81% of patients on LMWH (P < .001). Prescription copayments were higher on average for LMWH compared to DOACs (mean $153.61 versus 40.67; standard deviation $306.74 versus $33.11). ConclusionPatients remain on DOACs longer than LMWH, but medication adherence is similar with LMWH.
BackgroundEvery effort should be made to optimize surgical techniques and to minimize potential morbidity rates associated with live donor operations. Advances in a minimally invasive approach by robotic surgery to donor nephrectomy have raised the possibility of applying this technique to live donor bowel resections for intestinal transplantation.MethodsWe report the first 5 consecutive cases of a robotic-assisted live donor ileal segmentectomy. We describe the technical aspects of the procedure, discuss the rationale for considering this option, and evaluate potential advantages of this approach.ResultsWe found that this new approach is associated with less postoperative discomfort, a shorter hospital length of stay, and a faster recovery of bowel function compared to our previous open surgery.ConclusionsOur initial experience suggests that robotic surgery is a safe and feasible procedure for live donor ileal resection for intestinal transplantation and is a useful alternative to conventional open surgery.
SummaryThis paper is concerned with using multivariate binary observations to estimate the proportions of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple independent samples. Shorter distances over the tree between the leaves indicate higher similarity. We propose a novel data integrative extension to classical latent class models (LCMs) with tree-structured shrinkage. The proposed approach enables 1) borrowing of information across leaves, 2) estimating data-driven leaf groups with distinct vectors of class proportions, and 3) individual-level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class proportions than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.
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