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Ovarian cancer is a heterogeneous group of tumors in both cell type and natural history. While outcomes are generally favorable when detected early, the most common subtype, high-grade serous carcinoma (HGSOC), typically presents at an advanced stage and portends less favorable prognoses. Its aggressive nature has thwarted early detection efforts through conventional detection methods such as serum CA125 and ultrasound screening and thus inspired the investigation of novel biomarkers. Here, we report the systematic development of an extracellular-vesicle (EV)-based test to detect early-stage HGSOC. Our study is based on emerging insights into HGSOC biology, notably that it arises from precursor lesions within the fallopian tube before traveling to ovarian and/or peritoneal surfaces. To identify HGSOC marker candidates, we established murine fallopian tube (mFT) cells with oncogenic mutations inBrca1/2, Tp53, andPtengenes, and performed proteomic analyses on mFT EVs. The identified markers were then evaluated with an orthotopic HGSOC animal model. In serially-drawn blood samples of tumor-bearing mice, mFT-EV markers increased with tumor initiation, supporting their potential use in early cancer detection. A pilot human clinical study (n= 51) further narrowed EV markers to five candidates, EpCAM, CD24, VCAN, HE4, and TNC. Combined expression of these markers achieved high OvCa diagnostic accuracy (cancer vs. non-cancer) with a sensitivity of 0.89 and specificity of 0.93. The same five markers were also effective in a three-group classification: non-cancer, early-stage (I & II) HGSOC, and late-stage (III & IV) HGSOC. In particular, they differentiated early-stage HGSOC from the rest with a specificity of 0.91. Minimally invasive and repeatable, this EV-based testing could be a versatile and serial tool for informing patient care and monitoring women at high risk for ovarian cancer.

Supplemental material, sj-pdf-3-hss-10.1177_15563316221131251 for Does a Uni “Feel Better” than a Total Knee? Not Necessarily, When Using Modern Implant Designs by Michael P. Ast, David A. Kolin, Kaitlin M. Carroll, Destiny Davis, Andrew D. Pearle, David J. Mayman and Alvin C. Ong in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

Supplemental material, sj-pdf-2-hss-10.1177_15563316221131251 for Does a Uni “Feel Better” than a Total Knee? Not Necessarily, When Using Modern Implant Designs by Michael P. Ast, David A. Kolin, Kaitlin M. Carroll, Destiny Davis, Andrew D. Pearle, David J. Mayman and Alvin C. Ong in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

Supplemental material, sj-docx-1-hss-10.1177_15563316221131251 for Does a Uni “Feel Better” than a Total Knee? Not Necessarily, When Using Modern Implant Designs by Michael P. Ast, David A. Kolin, Kaitlin M. Carroll, Destiny Davis, Andrew D. Pearle, David J. Mayman and Alvin C. Ong in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

Supplemental material, sj-pdf-4-hss-10.1177_15563316221131251 for Does a Uni “Feel Better” than a Total Knee? Not Necessarily, When Using Modern Implant Designs by Michael P. Ast, David A. Kolin, Kaitlin M. Carroll, Destiny Davis, Andrew D. Pearle, David J. Mayman and Alvin C. Ong in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

Supplemental material, sj-pdf-7-hss-10.1177_15563316221131251 for Does a Uni “Feel Better” than a Total Knee? Not Necessarily, When Using Modern Implant Designs by Michael P. Ast, David A. Kolin, Kaitlin M. Carroll, Destiny Davis, Andrew D. Pearle, David J. Mayman and Alvin C. Ong in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

Supplemental material, sj-pdf-5-hss-10.1177_15563316221131251 for Does a Uni “Feel Better” than a Total Knee? Not Necessarily, When Using Modern Implant Designs by Michael P. Ast, David A. Kolin, Kaitlin M. Carroll, Destiny Davis, Andrew D. Pearle, David J. Mayman and Alvin C. Ong in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

Supplemental material, sj-pdf-6-hss-10.1177_15563316221131251 for Does a Uni “Feel Better” than a Total Knee? Not Necessarily, When Using Modern Implant Designs by Michael P. Ast, David A. Kolin, Kaitlin M. Carroll, Destiny Davis, Andrew D. Pearle, David J. Mayman and Alvin C. Ong in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

BACKGROUND: As the value of patient-reported outcomes becomes increasingly recognized, minimum clinically important difference (MCID) thresholds have seen greater use in shoulder arthroplasty. However, MCIDs are unique to certain populations, and variation in the modes of calculation in this field may be of concern. With the growing utilization of MCIDs within the field and value-based care models, a detailed appraisal of the appropriateness of MCID use in the literature is necessary and has not been systematically reviewed. QUESTIONS/PURPOSES: We performed a systematic review of MCID quantification in existing studies on shoulder arthroplasty to answer the following questions: (1) What is the range of values reported for the MCID in commonly used shoulder arthroplasty patient-reported outcome measures (PROMs)? (2) What percentage of studies use previously existing MCIDs versus calculating a new MCID? (3) What techniques for calculating the MCID were used in studies where a new MCID was calculated? METHODS: The Embase, PubMed, and Ovid/MEDLINE databases were queried from December 2008 through December 2020 for total shoulder arthroplasty and reverse total shoulder arthroplasty articles reporting an MCID value for various PROMs. Two reviewers (DAK, MAM) independently screened articles for eligibility, specifically identifying articles that reported MCID values for PROMs after shoulder arthroplasty, and extracted data for analysis. Each study was classified into two categories: those referencing a previously defined MCID and those using a newly calculated MCID. Methods for determining the MCID for each study and the variability of reported MCIDs for each PROM were recorded. The number of patients, age, gender, BMI, length of follow-up, surgical indications, and surgical type were extracted for each article. Forty-three articles (16,408 patients) with a mean (range) follow-up of 20 months (0.75 to 68) met the inclusion criteria. The median (range) BMI of patients was 29.3 kg/m(2) (28.0 to 32.2 kg/m(2)), and the median (range) age was 68 years (53 to 84). There were 17 unique PROMs with MCID values. Of the 112 MCIDs reported, the most common PROMs with MCIDs were the American Shoulder and Elbow Surgeons (ASES) (23% [26 of 112]), the Simple Shoulder Test (SST) (17% [19 of 112]), and the Constant (15% [17 of 112]) RESULTS: The ranges of MCID values for each PROM varied widely (ASES: 6.3 to 29.5; SST: 1.4 to 4.0; Constant: -0.3 to 12.8). Fifty-six percent (24 of 43) of studies used previously established MCIDs, with 46% (11 of 24) citing one study. Forty-four percent (19 of 43) of studies established new MCIDs, and the most common technique was anchor-based (37% [7 of 19]), followed by distribution (21% [4 of 19]). CONCLUSION: There is substantial inconsistency and variability in the quantification and reporting of MCID values in shoulder arthroplasty studies. Many shoulder arthroplasty studies apply previously published MCID values with variable ranges of follow-up rather than calculating population-specific thresholds. The use of previously calculated MCIDs may be acceptable in specific situations; however, investigators should select an anchor-based MCID calculated from a patient population as similar as possible to their own. This practice is preferable to the use of distribution-approach MCID methods. Alternatively, authors may consider using substantial clinical benefit or patient-acceptable symptom state to assess outcomes after shoulder arthroplasty. CLINICAL RELEVANCE: Although MCIDs may provide a useful effect-size based alternative to the traditional p value, care must be taken to use an MCID that is appropriate for the particular patient population being studied.

Supplemental material, sj-pdf-1-hss-10.1177_1556331620979984 for Perspective of Attending Physicians on the Use of Telemedicine in an Outpatient Arthroplasty Setting During the COVID-19 Pandemic by Samuel A. Taylor, Joseph D. Lamplot, David A. Kolin, Kaitlin M. Carroll, Kevin Plancher and Fred Cushner in HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery

ObjectiveTo explore both clinical and genetic risk factors for Covid-19 in a cohort from the United Kingdom.DesignProspective cohort study.Participants669 positive Covid-19 patients within a cohort of 502,536 UK Biobank participants, recruited between 2006 and 2010.Main Outcome MeasuresThe main outcome measure was Covid-19 positive status, determined by the presence of any positive test for a single individual. We also assessed risk factors for inpatient and outpatient status for Covid-19 positive individuals.ResultsWe found that black participants were at over three times increased risk of testing positive for Covid-19, relative to white participants, even after adjusting for confounders (adjusted relative risk [ARR] 3.14, 95% confidence interval [CI] 2.28 to 4.31). Asian participants were also at higher risk of Covid-19 (ARR 2.03, 95% CI 1.40 to 2.95). Next, we analyzed the association of comorbidities with Covid-19. We found that participants were at increased risk of Covid-19 if they had chronic obstructive pulmonary disease (ARR 1.54, 95% CI 1.02 to 2.31) or ischemic heart disease (ARR 1.56, 95% CI 1.18 to 2.07). However, there was no evidence that either angiotensin converting enzyme inhibitors (ARR 1.32, 95% CI 0.95 to 1.84) or angiotensin II receptor blockers (ARR 1.37, 95% CI 0.94 to 1.98) increased the risk of Covid-19. We confirmed that blood type A was associated with Covid-19 relative to blood type O individuals, and we also found that the HLA variant DQA1_509 was enriched in Covid-19 positive cases, even after Bonferroni correction (P = 1.0 x 10−5).ConclusionsIn this study, we found that black and Asian participants were at increased risk of Covid-19, even after adjusting for confounders. We also identified a novel genetic association with the HLA variant DQA1_509. Further investigations of genetic associations with Covid-19 may lead to important discoveries of genetic drivers of severe disease.

BACKGROUNDBoth clinical and genetic factors drive the risk of venous thromboembolism. However, whether clinically recorded risk factors and genetic variants can be combined into a clinically applicable predictive score remains unknown.METHODSUsing Cox proportional-hazard models, we analyzed the association of risk factors with the likelihood of venous thromboembolism in U.K. Biobank, a large prospective cohort. We created a novel ten point clinical score using seven established clinical risk factors for venous thromboembolism. We also generated a polygenic risk score of 21 single nucleotide polymorphisms to quantify genetic risk. The genetic score was categorized into high risk (top two deciles of scores), intermediate risk (deciles three to eight), and low risk (lowest two deciles). The discrete clinical score led to the following approximate decile categorizations: high risk (5 to 10 points), intermediate risk (3 to 4 points), and low risk (0 to 2 points).RESULTSAmongst the 502,536 participants in the U.K. Biobank, there were 4,843 events of venous thromboembolism. Analyses of established clinical risk factors and the most commonly used medications revealed that participants were at decreased risk of venous thromboembolism if they had ever used oral contraceptive pills (hazard ratio, 0.88; 95% confidence interval [CI], 0.79 to 0.99) or if they currently used bendroflumethiazide (hazard ratio, 0.84; 95% CI, 0.74 to 0.95), cod liver oil capsules (hazard ratio, 0.87; 95% CI, 0.77 to 0.99), or atenolol (hazard ratio, 0.79; 95% CI, 0.68 to 0.91). Participants were at significantly increased risk of venous thromboembolism if they were at high clinical risk (hazard ratio, 5.98; 95% CI, 5.43 to 6.59) or high genetic risk (hazard ratio, 2.28; 95% CI, 2.07 to 2.51) relative to participants at low clinical or genetic risk, respectively. Combining clinical risk factors with genetic risk factors produced a model that better predicted risk of venous thromboembolism than either model alone (PCONCLUSIONSBy assessing venous thromboembolic events in over 500,000 participants, we identified several known and novel associations between risk factors and venous thromboembolism. Participants in the high risk group of a combined score, consisting of clinical and genetic factors, were over eight times more likely to experience venous thromboembolism than participants in the low risk group.