Advanced enteropathy-associated T cell lymphoma (EATL) presenting with severe malabsorption and concomitantly diagnosed coeliac disease (CD)

Enteropathy-associated T cell lymphoma (EATL) is an aggressive subtype of non-Hodgkin's lymphoma often associated with coeliac disease (CD). We describe a previously healthy man in his 50 s who presented with a history of abdominal pain, failure to thrive and significant weight loss over a 3-month period. Investigations revealed a positive coeliac serology, diffuse duodenal atrophy with multiple duodenal and jejunal ulcers on endoscopy and mesenteric lymphadenopathy on CT imaging. Duodenal tissue biopsy confirmed a diagnosis of EATL Stage IVB. Chemotherapy with cyclophosphamide, doxorubicin, vincristine and prednisone regimen was initiated. This case highlights the need for greater awareness and consideration of EATL in individuals with worsening malabsorption and abdominal pain, irrespective of coeliac history.

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Respiratory disorders, being one of the leading causes of disability worldwide, account for constant evolution in management technologies, resulting in the incorporation of artificial intelligence (AI) in the recording and analysis of lung sounds to aid diagnosis in clinical pulmonology practice. Although lung sound auscultation is a common clinical practice, its use in diagnosis is limited due to its high variability and subjectivity. We review the origin of lung sounds, various auscultation and processing methods over the years and their clinical applications to understand the potential for a lung sound auscultation and analysis device. Respiratory sounds result from the intra-pulmonary collision of molecules contained in the air, leading to turbulent flow and subsequent sound production. These sounds have been recorded via an electronic stethoscope and analyzed using back-propagation neural networks, wavelet transform models, Gaussian mixture models and recently with machine learning and deep learning models with possible use in asthma, COVID-19, asbestosis and interstitial lung disease. The purpose of this review was to summarize lung sound physiology, recording technologies and diagnostics methods using AI for digital pulmonology practice. Future research and development in recording and analyzing respiratory sounds in real time could revolutionize clinical practice for both the patients and the healthcare personnel.

A Clinician's Guide to Running Custom Machine-Learning Models in an Electronic Health Record Environment

We recently brought an internally developed machine-learning model for predicting which patients in the emergency department would require hospital admission into the live electronic health record environment. Doing so involved navigating several engineering challenges that required the expertise of multiple parties across our institution. Our team of physician data scientists developed, validated, and implemented the model. We recognize a broad interest and need to adopt machine-learning models into clinical practice and seek to share our experience to enable other clinician-led initiatives. This Brief Report covers the entire model deployment process, starting once a team has trained and validated a model they wish to deploy in live clinical operations.

Practicing Digital Gastroenterology through Phonoenterography Leveraging Artificial Intelligence: Future Perspectives Using Microwave Systems

Production of bowel sounds, established in the 1900s, has limited application in existing patient-care regimes and diagnostic modalities. We review the physiology of bowel sound production, the developments in recording technologies and the clinical application in various scenarios, to understand the potential of a bowel sound recording and analysis device-the phonoenterogram in future gastroenterological practice. Bowel sound production depends on but is not entirely limited to the type of food consumed, amount of air ingested and the type of intestinal contractions. Recording technologies for extraction and analysis of these include the wavelet-based filtering, autoregressive moving average model, multivariate empirical mode decompression, radial basis function network, two-dimensional positional mapping, neural network model and acoustic biosensor technique. Prior studies evaluate the application of bowel sounds in conditions such as intestinal obstruction, acute appendicitis, large bowel disorders such as inflammatory bowel disease and bowel polyps, ascites, post-operative ileus, sepsis, irritable bowel syndrome, diabetes mellitus, neurodegenerative disorders such as Parkinson's disease and neonatal conditions such as hypertrophic pyloric stenosis. Recording and analysis of bowel sounds using artificial intelligence is crucial for creating an accessible, inexpensive and safe device with a broad range of clinical applications. Microwave-based digital phonoenterography has huge potential for impacting GI practice and patient care.

Artificial intelligence-enabled screening strategy for drug repurposing in monoclonal gammopathy of undetermined significance

Monoclonal gammopathy of undetermined significance (MGUS) is a benign hematological condition with the potential to progress to malignant conditions including multiple myeloma and Waldenstrom macroglobulinemia. Medications that modify progression risk have yet to be identified. To investigate, we leveraged machine-learning and electronic health record (EHR) data to screen for drug repurposing candidates. We extracted clinical and laboratory data from a manually curated MGUS database, containing 16,752 MGUS patients diagnosed from January 1, 2000 through December 31, 2021, prospectively maintained at Mayo Clinic. We merged this with comorbidity and medication data from the EHR. Medications were mapped to 21 drug classes of interest. The XGBoost module was then used to train a primary Cox survival model; sensitivity analyses were also performed limiting the study group to those with non-IgM MGUS and those with M-spikes >0.3 g/dl. The impact of explanatory features was quantified as hazard ratios after generating distributions using bootstrapping. Medication data were available for 12,253 patients; those without medications data were excluded. Our model achieved a good fit of the data with inverse probability of censoring weights concordance index of 0.883. The presence of multivitamins, immunosuppression, non-coronary NSAIDS, proton pump inhibitors, vitamin D supplementation, opioids, statins and beta-blockers were associated with significantly lower hazard ratio for MGUS progression in our primary model; multivitamins and non-coronary NSAIDs remained significant across both sensitivity analyses. This work could inform subsequent prospective studies, or similar studies in other disease states.

Demographic Trends in Emergency Department Visits for Psychiatric Concerns During the COVID-19 Pandemic

Objective

To describe changes in emergency department (ED) psychiatric visits during the pandemic in both rural and nonrural regions in the United States.

Methods

This cohort study was performed across 22 EDs in the Midwest and Southern United States from January 1, 2019 to April 22, 2021. Prevalence of psychiatric visits before and after the COVID-19 pandemic, defined as starting on March 1, 2020, were compared. Psychiatric and nonpsychiatric visits were defined on the basis of primary clinician-assigned diagnosis. The primary end point was average daily visits normalized to the average daily visit count before the pandemic, labeled as relative mean daily visits (RMDVs).

Results

Psychiatric visits decreased by 9% [RMDVs, 0.91; 95% confidence interval (CI), 0.89-0.93] during the pandemic period, whereas nonpsychiatric visits decreased by 17% (RMDVs, 0.83; 95% CI, 0.81-0.84). Black patients were the only demographic group with a significant increase in psychiatric visits during the pandemic (RMDVs, 1.12; 95% CI, 1.04-1.19). Periods of outbreaks of psychiatric emergencies were identified in most demographic groups, including among male and pediatric patients. However, the outbreaks detected among Black patients sustained the longest at 6 months. Unlike older adults who experienced outbreaks in the spring and fall of 2020, outbreaks among pediatric patients were detected later in 2021.

Conclusion

In this multisite study, total ED visits declined during the pandemic; however, psychiatric visits declined less than nonpsychiatric visits. Black patients experienced a greater increase in psychiatric emergencies than other demographic groups. There is also a concern for increasing outbreaks of pediatric psychiatric visits as the pandemic progresses.

Assessing the Generalizability of a Clinical Machine Learning Model Across Multiple Emergency Departments

Objective

To assess the generalizability of a clinical machine learning algorithm across multiple emergency departments (EDs).

Patients and Methods

We obtained data on all ED visits at our health care system's largest ED from May 5, 2018, to December 31, 2019. We also obtained data from 3 satellite EDs and 1 distant-hub ED from May 1, 2018, to December 31, 2018. A gradient-boosted machine model was trained on pooled data from the included EDs. To prevent the effect of differing training set sizes, the data were randomly downsampled to match those of our smallest ED. A second model was trained on this downsampled, pooled data. The model's performance was compared using area under the receiver operating characteristic (AUC). Finally, site-specific models were trained and tested across all the sites, and the importance of features was examined to understand the reasons for differing generalizability.

Results

The training data sets contained 1918-64,161 ED visits. The AUC for the pooled model ranged from 0.84 to 0.94 across the sites; the performance decreased slightly when Ns were downsampled to match those of our smallest ED site. When site-specific models were trained and tested across all the sites, the AUCs ranged more widely from 0.71 to 0.93. Within a single ED site, the performance of the 5 site-specific models was most variable for our largest and smallest EDs. Finally, when the importance of features was examined, several features were common to all site-specific models; however, the weight of these features differed.

Conclusion

A machine learning model for predicting hospital admission from the ED will generalize fairly well within the health care system but will still have significant differences in AUC performance across sites because of site-specific factors.

Practical development and operationalization of a 12-hour hospital census prediction algorithm

Hospital census prediction has well-described implications for efficient hospital resource utilization, and recent issues with hospital crowding due to CoVID-19 have emphasized the importance of this task. Our team has been leading an institutional effort to develop machine-learning models that can predict hospital census 12 hours into the future. We describe our efforts at developing accurate empirical models for this task. Ultimately, with limited resources and time, we were able to develop simple yet useful models for 12-hour census prediction and design a dashboard application to display this output to our hospital’s decision-makers. Specifically, we found that linear models with ElasticNet regularization performed well for this task with relative 95% error of +/− 3.4% and that this work could be completed in approximately 7 months.

An under-recognized phenomenon: Myocardial volume change during the cardiac cycle

BACKGROUND

Myocardial volume is assumed to be constant over the cardiac cycle in the echocardiographic models used by professional guidelines, despite evidence that suggests otherwise. The aim of this paper is to use literature-derived myocardial strain values from healthy patients to determine if myocardial volume changes during the cardiac cycle.

METHODS

A systematic review for studies with longitudinal, radial, and circumferential strain from echocardiography in healthy volunteers ultimately yielded 16 studies, corresponding to 2917 patients. Myocardial volume in systole (MVs) and diastole (MVd) was used to calculate MVs/MVd for each study by applying this published strain data to three models: the standard ellipsoid geometric model, a thin-apex geometric model, and a strain-volume ratio.

RESULTS

MVs/MVd<1 in 14 of the 16 studies, when computed using these three models. A sensitivity analysis of the two geometric models was performed by varying the dimensions of the ellipsoid and calculating MVs/MVd. This demonstrated little variability in MVs/MVd, suggesting that strain values were the primary determinant of MVs/MVd rather than the geometric model used. Another sensitivity analysis using the 97.5th percentile of each orthogonal strain demonstrated that even with extreme values, in the largest two studies of healthy populations, the calculated MVs/MVd was <1.

CONCLUSIONS

Healthy human myocardium appears to decrease in volume during systole. This is seen in MRI studies and is clinically relevant, but this study demonstrates that this characteristic was also present but unrecognized in the existing echocardiography literature.

A Living, Interactive Systematic Review and Network Meta-analysis of First-line Treatment of Metastatic Renal Cell Carcinoma

CONTEXT

Identifying the most effective first-line treatment for metastatic renal cell carcinoma (mRCC) is challenging as rapidly evolving data quickly outdate the existing body of evidence, and current approaches to presenting the evidence in user-friendly formats are fraught with limitations.

OBJECTIVE

To maintain living evidence for contemporary first-line treatment for previously untreated mRCC.

EVIDENCE ACQUISITION

We have created a living, interactive systematic review (LISR) and network meta-analysis for first-line treatment of mRCC using data from randomized controlled trials comparing contemporary treatment options with single-agent tyrosine kinase inhibitors. We applied an advanced programming and artificial intelligence-assisted framework for evidence synthesis to create a living search strategy, facilitate screening and data extraction using a graphical user interface, automate the frequentist network meta-analysis, and display results in an interactive manner.

EVIDENCE SYNTHESIS

As of October 22, 2020, the LISR includes data from 14 clinical trials. Baseline characteristics are summarized in an interactive table. The cabozantinib + nivolumab combination (CaboNivo) is ranked the highest for the overall response rate, progression-free survival, and overall survival, whereas ipilimumab + nivolumab (NivoIpi) is ranked the highest for achieving a complete response (CR). NivoIpi, and atezolizumab + bevacizumab (AteBev) were ranked highest (lowest toxicity) and CaboNivo ranked lowest for treatment-related adverse events (AEs). Network meta-analysis results are summarized as interactive tables and plots, GRADE summary-of-findings tables, and evidence maps.

CONCLUSIONS

This innovative living and interactive review provides the best current evidence on the comparative effectiveness of multiple treatment options for patients with untreated mRCC. Trial-level comparisons suggest that CaboNivo is likely to cause more AEs but is ranked best for all efficacy outcomes, except NivoIpi offers the best chance of CR. Pembrolizumab + axitinib and NivoIpi are acceptable alternatives, except NivoIpi may not be preferred for patients with favorable risk. Although network meta-analysis provides rankings with statistical adjustments, there are inherent biases in cross-trial comparisons with sparse direct evidence that does not replace randomized comparisons.

PATIENT SUMMARY

It is challenging to decide the best option among the several treatment combinations of immunotherapy and targeted treatments for newly diagnosed metastatic kidney cancer. We have created interactive evidence summaries of multiple treatment options that present the benefits and harms and evidence certainty for patient-important outcomes. This evidence is updated as soon as new studies are published.

Cardiac Abnormalities in COVID-19 and Relationship to Outcome

OBJECTIVE

To characterize the clinical and transthoracic echocardiographic features and 30-day outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19).

METHODS

Retrospective cohort study that included consecutive inpatients with COVID-19 infection who underwent clinically indicated transthoracic echocardiography at 10 sites in the Mayo Clinic Health System between March 10 and August 5, 2020. Echocardiography was performed at bedside by cardiac sonographers according to an abbreviated protocol. Echocardiographic results, demographic characteristics, laboratory findings, and clinical outcomes were analyzed.

RESULTS

There were 179 patients, aged 59.8±16.9 years and 111 (62%) men; events within 30 days occurred in 70 (39%) patients, including prolonged hospitalization in 43 (24%) and death in 27 (15%). Echocardiographic abnormalities included left ventricular ejection fraction less than 50% in 29 (16%), regional wall motion abnormalities in 26 (15%), and right ventricular systolic pressure (RVSP) of 35 or greater mm Hg in 44 (44%) of 101 in whom it was measured. Myocardial injury, defined as the presence of significant troponin level elevation accompanied by new ventricular dysfunction or electrocardiographic abnormalities, was present in 13 (7%). Prior echocardiography was available in 36 (20%) patients and pre-existing abnormalities were seen in 28 (78%) of these. In a multivariable age-adjusted model, area under the curve of 0.81, prior cardiovascular disease, troponin level, D-dimer level, and RVSP were related to events at 30 days.

CONCLUSION

Bedside Doppler assessment of RVSP appears promising for short-term risk stratification in hospitalized patients with COVID-19 infection undergoing clinically indicated echocardiography. Pre-existing echocardiographic abnormalities were common; caution should be exercised in attributing such abnormalities to the COVID-19 infection in this comorbid patient population.

A framework for living evidence synthesis in cancer: Living, interactive network meta-analysis for first-line treatment of metastatic renal cell carcinoma (mRCC)

335

Background: Systematic reviews are outdated quickly when the evidence is rapidly evolving as the process is laborious and there is little incentive for primary author team of an index SRMA to update the evidence. Consequently, there is an epidemic of redundant SRMAs performed by different teams—sometimes with conflicted results—for treatment of first line mRCC. Methods: We have created a living, interactive systematic review (LISR)and network meta-analysis(LINMA) for the treatment of first line mRCC using an Artificial intelligence (AI) assisted framework for evidence synthesis (Living, Interactive evidence synthesis framework) (LIvE) . The framework is implemented in five-layered architecture (application layer, shared module layer, core service layer, middleware layer, and storage layer) which work together to automate the identification of new studies and analysis and semi-automate the screening and data extraction. Dynamic features such as interactive tables, figures and evidence maps are enabled using Python and JavaScript programming languages. Results: We have maintained a living, interactive evidence profile for the first line treatment mRCC since September 2019 ( LIVING WEBSITE) . Living search strategy identifies new studies as they become available. As of October 13, 2020 LISR, includes data 14 clinical trials ( PRISMA ). Baseline characteristics are summarized in an interactive table ( TABLE) . Cabozantinib& Nivolumab (Cabo-Nivo) is the highest ranked drug for improving Overall Response (OR), Progression Free Survival (PFS) and Overall Survival (OS) whereas Ipilimumab in combination with Nivolumab (Ipi-Nivo) is highest ranked drug for achieving complete response (CR). Ipi-Nivo and Atezolizumab & Bevacizumab (Ate-Bev) ranked highest and Cabo-Nivo ranked lowest for treatment related Adverse events (TRAEs). Results of network meta-analysis are summarized as interactive tables and plots ( NMA ), summary of findings tables ( MULTIPLE COMAPRISONS ) and evidence maps ( MAP ). Conclusions: LISRs can potentially reduce redundancy, increase transparency, reproducibility, enable shared-decision making (at a guideline level, or in a patient-clinician dyad) and support living guidelines.

Cardiac MRI demonstrates compressibility in healthy myocardium but not in myocardium with reduced ejection fraction

BACKGROUND

The professional guidelines assume that the myocardial volume in systole (MVs) is equal to that in diastole (MVd), despite some limited evidence that points to the contrary. The aim of this manuscript is to determine whether this is true in healthy myocardium using gold standard cardiac MRI, as well as transthoracic echocardiography (TTE). The secondary aim is to determine whether there are similar MV changes in patients with heart failure with reduced ejection fraction (HFrEF).

METHOD

A prospectively derived cohort at Mayo Clinic of 115 adult subjects (mean age 42.8 years, 58% female) with no cardiac risk factors was identified. Cardiac MRI was obtained on all 115 patients, 51 of whom also consented to a TTE. MRI from a retrospectively derived cohort of 50 HFrEF patients was also collected. MVs and MVd was calculated using standard approaches with inclusion of the papillary muscles.

RESULTS

In the healthy population, MRI demonstrated MVs/MVd = 0.87 (SD 0.04) and TTE demonstrated MVs/MVd = 0.79 (SD 0.07), suggesting compressibility (p < 0.0001). In the 51 healthy patients who received both imaging modalities, MVs/MVd was 8.0% higher in MRI than TTE (p < 0.0001), but both modalities had MVs/MVd < 1 (p < 0.0001). A Bland-Altman plot demonstrated that as the mean MVs/MVd increases, the difference in MVs/MVd MRI-TTE declines (r = -0.53, p < 0.0001). However, in HFrEF populations, MVs/MVd = 1.01 (0.03), suggesting myocardial incompressibility.

CONCLUSION

Contrary to currently accepted standards, healthy myocardium is compressible but HFrEF myocardium is incompressible. The ratio MVs/MVd merits further study in an expanded normal cohort and in disease states.

Systolic-to-diastolic myocardial volume ratio as a novel imaging marker of cardiomyopathy

BACKGROUND

In patients with normal left ventricular ejection fraction, it may be difficult to distinguish between the normal and diseased heart. Novel assessments of ventricular function, such as extracellular volume imaging, myocardial perfusion imaging and myocardial contraction fraction are emerging to better assess disease burden in these cases. This study endeavored to determine whether the ratio of myocardial volume in systole to myocardial volume in diastole (MVs/MVd), differs between normal hearts and those with disease states characterized by normal ejection fraction.

METHOD

Consecutive patients from 2008 to 2018 with hypertrophic cardiomyopathy (HCM), cardiac amyloidosis, and heart failure with preserved ejection fraction (HFpEF) who underwent cardiac magnetic resonance imaging (MRI) were selected for inclusion, along with a sex- and age-matched cohort of normal volunteers who also underwent cardiac MRI. Manual tracings were performed on each MRI to calculate MVs/MVd, which was then compared across subgroups.

RESULTS

Included were 50 patients with HCM, 50 patients with cardiac amyloidosis, 26 patients with HFpEF, and 30 normal subjects. Age was 54.1 years (SD 16.7); mean MVs/MVd was 0.88 (SD 0.04) in the normal subgroup, 1.03 (SD 0.06) in HCM patients, 1.03 (SD 0.06) in cardiac amyloidosis patients, and 0.97 (SD 0.02) in HFpEF patients, with all pathology subgroups different from the normal subgroup (p < .0001 for each). The ratio of MVs/MVd discriminated diseased from normal with c statistic 0.989 (p < .001).

CONCLUSIONS

This study suggests that a novel and easily-captured metric of ventricular function, MVs/MVd, can differentiate normal ventricular function from multiple cardiomyopathies with normal ejection fractions.

The Current Hepatic Encephalopathy Pipeline

Hepatic encephalopathy (HE) is a complication of acute or chronic liver failure; its mechanism is complex, involving multiple organ systems, and is still being elucidated. The standard of care, lactulose, has remained generally unchanged for decades. However, in recent years, better understanding of the pathophysiology has yielded new therapeutic targets for this reversible condition. These novel treatments act both on traditional pathways established in the ammonia hypothesis and through more recently discovered mechanisms. Here, we review contemporary investigational therapies for HE. We used narrative reviews and searched ClinicalTrials.gov database for the condition "hepatic encephalopathy" through August 29, 2019. Our review yielded six key areas of therapeutic focus: (1) antibiotics against urease-producing gut bacteria, (2) intravenous ammonia scavengers, (3) modified synthetic probiotics, (4) fecal microbiota transplant, (5) brain steroid-modulating agents, and 6) nonlactulose laxatives. Active trials are ongoing in each of these therapeutic areas.

Cost-effectiveness of novel antiandrogens (AAs) for treatment of nonmetastatic castrate-resistant prostate cancer (nmCRPC)

5583

Background: FDA has approved three novel AAs [Apalutamide(A), Darolutamide(D) and Enzalutamide(E)] in combination with Androgen deprivation therapy ( ADT) for treatment of (nmCRPC) patients (pts). We report the cost-effectiveness of these drugs from the US perspective to help facilitate the choice of these agents for clinical practice. Methods: A life time Markov state-transition model was constructed with three health states (Metastasis-Free Survival[MFS], Metastatic disease, and Death) to compare cost-effectiveness of AA therapies for treatment of nmCRPC based on US healthcare payer perspective. A network meta-analysis of MFS and OS was conducted due to the lack of head to head trials. An approximation of the original individual-level patient time-to-event data were derived from digitized Kaplan-Meier curves for OS and MFS. Weibull distributions was selected as the best fitted model fitted and extrapolated as per the NICE decision support unit recommendations. Medication costs were based on wholesale acquisition cost. Adverse event (AE) grades 3/4 management costs were incorporated in the model. Discount rate of 3% per year was applied to costs and effects. Life years (LYs) and quality adjusted life years (QALYs) for each treatment as well as the incremental cost effectiveness (ICER) and cost utility (ICUR) ratios were estimated. Base case analyses (BCA) and probabilistic sensitivity analyses (PSA) were estimated. Results: The table summarizes the results form BCA analyses. A+ADT offers best gain in LYs (8.37yrs) and QALYs (5.30 yrs) but at higher cost. Conclusions: Apalutamide was associated with gains in LYs and QALYs traded off with higher lifetime cost relative to other AA alternatives. ADT was associated with lower gains in LYs and QALYs traded off with lower lifetime cost relative to other alternatives. Based on a $150,000/QALY threshold pay off, A+ADT is likely more cost effective compared to E+ADT or ADT alone; while E+ ADT may be more cost effective compared to D+ ADT. [Table: see text]

Adjuvant therapy in high-risk renal cell cancer: A systematic review and cumulative meta-analysis

708

Background: Patients with high risk non-metastatic renal cell cancer (RCC) are at significant risk of recurrence following nephrectomy. Previously, we reported no benefit of adjuvant tyrosine kinase inhibitor (TKI) treatment in high-risk patients. Since our most recent publication, efficacy results from the multicenter double-blind SORCE trial have become available. We updated our meta-analysis to include these additional data and performed a cumulative meta-analysis. Methods: PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials were searched to identify relevant RCTs. A generic variance-weighted random effects model was used to derive estimates for efficacy. Heterogeneity was assessed using the Cochran Q statistic and was quantified using the I2 test. The primary outcome was disease-free survival (DFS), defined as the interval between randomization and the first recurrence, the occurrence of metastasis or a secondary cancer, or death due to any cause. Statistical analysis was performed using Comprehensive Meta-Analysis version 3 (Biostat). Results: Five phase 3 trials were identified, enrolling 6531 patients. Two trials compared sunitinib with placebo (S-TRAC and ECOG-ACRIN), two compared sorafenib with placebo (ECOG-ACRIN and SORCE) and one trial each compared pazopanib (PROTECT) and axitinib (ATLAS) vs placebo. Cumulative evidence suggests that adjuvant therapy with TKIs showed no significant improvement in (DFS) hazard ratio [HR] of 0.93 (95% CI, 0.85-1.02), compared to placebo. There was no significant heterogeneity among included trials ( I2= 52%, P= .41). Overall, the trials were at low risk of bias. Conclusions: Adjuvant vascular endothelial growth factor tyrosine kinase inhibitors in high-risk renal cell carcinoma did not improve DFS as compared to placebo. Improved patient selection using better prognostic biomarkers or scoring systems may identify subsets of patients who can benefit from adjuvant treatments. Toxicity estimates will be updated as data from SORCE trial publication becomes available.

A systematic review and network meta-analysis of first-line treatment options in patients metastatic renal cell carcinoma

709

Background: Several immunotherapy (IMT) combinations either as an IMT doublet or IMT in combination with TKIs are now available for first-line therapy of metastatic renal cell carcinoma (mRCC). In the absence of head-to-head clinical trials, we performed an indirect comparison of frontline treatment options to provide clinical guidance. Methods: Medline, Embase and Cochrane Library were searched to identify relevant trials. Hazard ratios (HR) and confidence interval (CI) for primary outcome of progression-free survival (PFS) and secondary outcome of overall survival (OS) were abstracted. Network meta-analysis was performed using a multivariate, consistency model, random-effects meta-regression. Data on Grade 3 or higher AEs was abstracted and meta-analyzed. Pre-specified subgroup analyses were performed based on risk categories (high risk vs low and intermediate vs), history of prior nephrectomy, PD-L1 positivity, age and sex. Risk for bias(RoB) was assessed using the Cochrane Collaboration’s tool. Results: Nine studies were included for PFS analysis, and 6 studies for OS analysis. Avelumab-axitinib (AA) (HR 0.69, 0.48-0.96), and Pembrolizumab-Axitinib (PA) (HR 0.89, 0.50-0.96) significantly improved PFS, while there was no significant PFS benefit with atezolizumab-bevacizumab (AB) (HR 0.83, 0.62-1.13) and nivolumab-ipilimumab (NI) (HR 0.85, 0.63-1.15) as compared to Sunitinib. PA (HR 0.53, 0.38-0.75) and NI (HR 0.63, 0.44-0.90) significantly improved OS, while AB (HR 0.93, 0.75-1.12) showed no significant OS benefit as compared to Sunitinib. NI and AB had significantly fewer grade ≥3 AE than sunitinib. No significant interaction was found by risk group, age, sex or prior nephrectomy. Significant interaction was found by PD-L1 expression(p<0.001), with significant PFS improvement in PD-L1 positive (HR 0.62, 0.53-0.73) but not in PD-L1 negative patients (HR 0.92, 0.81-1.05). Overall, RoB was low amongst included studies. Conclusions: AA improved PFS, NI improved OS, whereas PA improve both PFS and OS as compared to sunitinib monotherapy. However, no IMT combination was superior to other combinations. Cost effectiveness analysis will be reported separately.

Clinico-radiologic Features of Lung Disease Associated With Aspiration Identified on Lung Biopsy

BACKGROUND

Aspiration-related lung diseases are commonly diagnosed presumptively based on the clinical context and radiologic findings. Limited data exist on the spectrum of clinico-radiologic presentations associated with aspiration.

METHODS

This study reviewed all cases of aspiration identified on lung biopsy encountered at the Mayo Clinic between 2003 and 2017. Demographic and clinical features, including risk factors for aspiration, diagnoses suspected prior to biopsy, imaging findings, and microbiologic data, were analyzed.

RESULTS

A total of 52 consecutive adult cases of aspiration identified on lung biopsy (histologic presence of food or other particulate matter) were included; patients' median age was 59 years (range, 22 to 79 years), 38% were women, and there were five lung transplant recipients. Of these, 63% were diagnosed according to results of surgical biopsy (including four cases of lobectomy) and 37% according to results of transbronchial biopsy. Aspiration was clinically suspected prior to biopsy in 35% of the subjects. Ninety percent of subjects had at least one identifiable risk factor for aspiration; gastroesophageal reflux disease was the most common (62%), followed by a structurally abnormal esophagogastric tract and the use of consciousness-impairing medications. Only 27% of patients reported dysphagia or choking. Chest CT imaging revealed a variety of parenchymal patterns, including bronchiolitis (42%), patchy consolidation (19%), and mass (15%). Of 25 patients undergoing a video-swallow evaluation, 14 (56%) had abnormal results with laryngeal penetration with or without aspiration. Microbial cultures obtained in 21 lung biopsy specimens yielded no pathogens.

CONCLUSIONS

Aspiration can occur in the absence of subjective or demonstrable swallowing difficulties and manifest a broad spectrum of clinico-radiologic presentations.

Spectrum of Chronic Complications Related to Silicone Leakage and Migration

BACKGROUND

Medical silicone is widely used as implants and free injections, but the spectrum of complications related to migration or embolization of silicone remains unclear.

METHODS

We retrospectively reviewed 79 patients with silicone migration as confirmed on pathology between January 1, 2001, and December 31, 2016. The presenting clinical and imaging features, diagnostic testing, treatment, and outcome were assessed.

RESULTS

Nearly all patients were women, and 43% had a history of breast cancer. Sixty-three cases (80%) consisted of localized silicone granulomas, including 1 patient who developed severe hypercalcemia related to the granulomatous reaction. The remaining 16 cases (20%) involved migration of silicone to regional lymph nodes or distant tissue and included 1 case of chronic silicone pneumonitis. These complications were detected many years (median, 22 years; range, 1-40 years) after initial silicone placement. Only magnetic resonance imaging, dual-energy computed tomography (CT), and ultrasonography demonstrated specificity for detection of silicone in lymph nodes and soft tissues. Other modalities including positron emission tomography, single-energy CT, and mammography detected only nonspecific abnormalities. Excisional biopsy of symptomatic lymphadenopathy or masses usually led to resolution of symptoms. The patient with silicone pneumonitis improved with corticosteroid therapy.

CONCLUSIONS

Chronic complications related to silicone extravasation and migration can present with local or distant manifestations, typically encountered many years after the original silicone placement. Magnetic resonance imaging, dual-energy CT, and ultrasonography are helpful for noninvasive diagnosis.

Policy makers will need a way to update bundled payments that reflects highly skewed spending growth of various care episodes

Bundled payment entails paying a single price for all services delivered as part of an episode of care for a specific condition. It is seen as a promising way to slow the growth of health care spending while maintaining or improving the quality of care. To implement bundled payment, policy makers must set base payment rates for episodes of care and update the rates over time to reflect changes in the costs of delivering care and the components of care. Adopting the fee-for-service paradigm of adjusting payments with uniform update rates would be fair and accurate if costs increased at a uniform rate across episodes. But our analysis of 2003 and 2007 US commercial claims data showed spending growth to be highly skewed across episodes: 10 percent of episodes accounted for 82.5 percent of spending growth, and within-episode spending growth ranged from a decline of 75 percent to an increase of 323 percent. Given that spending growth was much faster for some episodes than for others, a situation known as skewness, policy makers should not update episode payments using uniform update rates. Rather, they should explore ways to address variations in spending growth, such as updating episode payments one by one, at least at the outset.

The slowdown in health care spending in 2009-11 reflected factors other than the weak economy and thus may persist

During and immediately after the recent recession, national health expenditures grew exceptionally slowly. During 2009-11 per capita national health spending grew about 3 percent annually, compared to an average of 5.9 percent annually during the previous ten years. Policy experts disagree about whether the slower health spending growth was temporary or represented a long-term shift. This study examined two factors that might account for the slowdown: job loss and benefit changes that shifted more costs to insured people. Based on an examination of data covering more than ten million enrollees with health care coverage from large firms in 2007-11, we found that these enrollees' out-of-pocket costs increased as the benefit design of their employer-provided coverage became less generous in this period. We conclude that such benefit design changes accounted for about one-fifth of the observed decrease in the rate of growth. However, we also observed a slowdown in spending growth even when we held benefit generosity constant, which suggests that other factors, such as a reduction in the rate of introduction of new technology, were also at work. Our findings suggest cautious optimism that the slowdown in the growth of health spending may persist--a change that, if borne out, could have a major impact on US health spending projections and fiscal challenges facing the country.

Caveolin-1 and force regulation in porcine airway smooth muscle

Caveolae are specialized membrane microdomains expressing the scaffolding protein caveolin-1. We recently demonstrated the presence of caveolae in human airway smooth muscle (ASM) and the contribution of caveolin-1 to intracellular calcium ([Ca(2+)](i)) regulation. In the present study, we tested the hypothesis that caveolin-1 regulates ASM contractility. We examined the role of caveolins in force regulation of porcine ASM under control conditions as well as TNF-α-induced airway inflammation. In porcine ASM strips, exposure to 10 mM methyl-β-cyclodextrin (CD) or 5 μM of the caveolin-1 specific scaffolding domain inhibitor peptide (CSD) resulted in time-dependent decrease in force responses to 1 μM ACh. Overnight exposure to the cytokine TNF-α (50 ng/ml) accelerated and increased caveolin-1 expression and enhanced force responses to ACh. Suppression of caveolin-1 with small interfering RNA mimicked the effects of CD or CSD. Regarding mechanisms by which caveolae contribute to contractile changes, inhibition of MAP kinase with 10 μM PD98059 did not alter control or TNF-α-induced increases in force responses to ACh. However, inhibiting RhoA with 100 μM fasudil or 10 μM Y27632 resulted in significant decreases in force responses, with lesser effects in TNF-α exposed samples. Furthermore, Ca(2+) sensitivity for force generation was substantially reduced by fasudil or Y27632, an effect even more enhanced in the absence of caveolin-1 signaling. Overall, these results indicate that caveolin-1 is a critical player in enhanced ASM contractility with airway inflammation.