16 research outputs found
The Splinternet
No full textMark A. Lemley, the William H. Neukom Professor of Law at Stanford Law School and the Director of the Stanford Program in Law, Science and Technology, delivers the 2020 David L. Lange Lecture on Intellectual Property, The Splinternet. Professor Lemley teaches intellectual property, patent law, trademark law, antitrust, the law of robotics and AI, video game law, and remedies. He is the author of eight books and 173 articles, including the two-volume treatise IP and Antitrust , and his works have been cited more than 270 times by courts, including 15 times by the United States Supreme Court, and more than 16,000 times in books and law review articles, making him the most-cited scholar in IP law and one of the five most cited legal scholars of all time. Professor Lemley is also a founding partner of Durie Tangri LLP and a founder of Lex Machina, Inc., a startup company that provides litigation data and analytics to law firms, companies, courts, and policymakers. Sponsored by the Office of the Dean
Progress in risk prediction for people with chronic kidney disease.
No full textAuthor(s) Pre Print Version OnlyPURPOSE OF REVIEW: Chronic kidney disease is common, but the associated risk of adverse outcomes is heterogeneous and methods for risk stratification are, therefore, required. We have reviewed recent progress in developing clinically applicable risk scores for people with chronic kidney disease. RECENT FINDINGS: Large epidemiological studies have confirmed that lower glomerular filtration rate and albuminuria are the most important risk factors for adverse outcomes in all populations studied. Ongoing research has identified several potentially important novel risk factors, including genetic factors, metabolomic factors, fibroblast growth factor 23, novel cardiovascular risk factors [CXC motif, ligand 12 (CXCL12) and ceruloplasmin], skin autofluorescence and inflammatory markers (serum-free light chains and circulating receptors for tumour necrosis factor). Several risk scores have been developed and one in particular (by Tangri et al.) performs well, uses variables commonly assessed in clinical practice and has been externally validated. Further studies are required to assess its performance in populations outside of secondary care and its usefulness in guiding decision making in clinical practice. SUMMARY: Although substantial progress has been made, the goal of achieving simple robust risk scores which are widely applicable and effective in guiding clinical decision making remains to be achieved
Patient and Clinician Perspectives: To Create a Better Future for Chronic Kidney Disease, We Need to Talk About Our Kidneys
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The above Infographic and Video Abstract represents the opinions of the authors. For a full list of declarations, including funding and author disclosure statements, and copyright information, please see the full text online. (see “read the peer-reviewed publication” opposite). </div
Is trabecular bone score associated with appendicular lean mass?
No full textAmong individuals aged ≥ 40 years old, we found that after controlling for age, sex, FMI, and tissue thickness, an increase of 1kg/m2 of ALMI is associated with an increase in TBS of 0.058, which is approximately half of one population standard deviation, or 4.7% of the average value for TBS.
Trabecular bone score (TBS) has been shown to be an independent risk factor for fracture. Muscle pulling on bone is hypothesized to be a mechanical stimulus for osteogenesis. Our aim was to explore whether TBS is associated with appendicular lean mass index (ALMI, appendicular lean mass divided by height squared, units kg/m2).
We used visit data from individuals aged 40 years and older in the Manitoba DXA Registry (February 1999-March 2016). ALMI, total body lean mass index (LMI) and total body fat mass index (FMI) were estimated from weight, sex, and percent fat from spine and hip DXA (all R2 > 0.85 vs total body DXA). We used linear and logistic regression analyses to examine cross-sectional associations between ALMI or LMI and TBS in analyses adjusted for age and sex, and age, sex, FMI, and abdominal tissue thickness.
Among 60,196 individuals (90% female), descriptive statistics as mean (SD) were: TBS 1.245 (0.122), BMI 26.4 kg/m2 (4.4), ALMI 6.7 kg/m2 (0.9), LMI 15.3 kg/m2 (1.7) and FMI kg/m2 10.0 (3.3). ALMI was associated with TBS after adjustment for age and sex (Unstandardized β = 0.007, 95%CI 0.006 to 0.008, Adjusted R2 = 0.130, p 2 = 0.557, p 2 of ALMI was associated with an increase in TBS of 0.058, approximately half of one population standard deviation, or 4.7% of the average value for TBS. Meeting the EWGSOP2 criterion for sarcopenia was associated with being in the lowest TBS tertile after adjustment for age, sex and FMI with odds ratio 1.46 (95% CI 1.38 to 1.55).
ALMI was associated with TBS after controlling for age, sex, FMI, and abdominal tissue thickness.
© 2025. The Author(s), under exclusive licence to the International Osteoporosis Foundation and the Bone Health and Osteoporosis Foundation
Patient management and clinical outcomes associated with a recorded diagnosis of stage 3 chronic kidney disease: the REVEAL-CKD study
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Dapagliflozin Utilization in Chronic Kidney Disease and Its Real-World Effectiveness Among Patients with Lower Levels of Albuminuria in the USA and Japan
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The above Graphical Abstract and Video Abstract represents the opinions of the authors. For a full list of declarations, including funding and author disclosure statements, and copyright information, please see the full text online. (see “read the peer-reviewed publication” opposite). </p
Does biomarker use in oncology improve clinical trial failure risk? A large‐scale analysis
No full textTo date there has not been an extensive analysis of the outcomes of biomarker use in oncology.
Data were pooled across four indications in oncology drawing upon trial outcomes from www.clinicaltrials.gov: breast cancer, non-small cell lung cancer (NSCLC), melanoma and colorectal cancer from 1998 to 2017. We compared the likelihood drugs would progress through the stages of clinical trial testing to approval based on biomarker status. This was done with multi-state Markov models, tools that describe the stochastic process in which subjects move among a finite number of states.
Over 10000 trials were screened, which yielded 745 drugs. The inclusion of biomarker status as a covariate significantly improved the fit of the Markov model in describing the drug trajectories through clinical trial testing stages. Hazard ratios based on the Markov models revealed the likelihood of drug approval with biomarkers having nearly a fivefold increase for all indications combined. A 12, 8 and 7-fold hazard ratio was observed for breast cancer, melanoma and NSCLC, respectively. Markov models with exploratory biomarkers outperformed Markov models with no biomarkers.
This is the first systematic statistical evidence that biomarkers clearly increase clinical trial success rates in three different indications in oncology. Also, exploratory biomarkers, long before they are properly validated, appear to improve success rates in oncology. This supports early and aggressive adoption of biomarkers in oncology clinical trials
Grams ME, Sang Y, Ballew SH, et al, for the Chronic Kidney Disease Prognosis Consortium. Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. Kidney Int. 2018;93:1442–1451
No full textThe Chronic Kidney Disease (CKD) Prognosis Consortium is a collaborative author of the above-mentioned article. The CKD Prognosis Consortium investigators/collaborators are as follows: • African American Study of Kidney Disease and Hypertension (AASK): Brad Astor, Lawrence J. Appel; Canadian Study of Prediction of Death, Dialysis and Interim Cardiovascular Events (CanPREDDICT): Adeera Levin, Mila Tang, Ognjenka Djurdjev; Cleveland Clinic CKD Registry Study (CCF): Sankar D. Navaneethan, Stacey E. Jolly, Jesse D. Schold, Joseph V. Nally Jr.; Chronic Renal Impairment in Birmingham (CRIB): David C. Wheeler, Jonathan Emberson, John Townend, Martin Landray; Chronic Renal Insufficiency Cohort Study (CRIC): Harold I. Feldman, Chi-yuan Hsu, James P. Lash, Lawrence J. Appel; Chronic Renal Insufficiency Standards Implementation Study (CRISIS): Philip A. Kalra, James P. Ritchie, Raman Maharajan, Rachel J. Middleton, Donal J. O'Donoghue; German Chronic Kidney Disease Study (GCKD): Kai-Uwe Eckardt, Markus P. Schneider, Anna Köttgen, Florian Kronenberg, Barbara Bärthlein; Geisinger Health System: Alex R. Chang, Jamie A. Green, H. Lester Kirchner, Kevin Ho; Grampian Laboratory Outcomes, Morbidity and Mortality Studies – 2 (GLOMMS2): Angharad Marks, Corri Black, Gordon J. Prescott, Nick Fluck; Gonryo Study: Masaaki Nakayama, Mariko Miyazaki, Tae Yamamoto, Gen Yamada; Hong Kong CKD Studies: Angela Yee-Moon Wang, Sharon Cheung, Sharon Wong, Jessie Chu, Henry Wu; Ontario Institute for Clinical Evaluative Sciences, Provincial Kidney, Dialysis and Transplantation program (ICES KDT): Amit X. Garg, Eric McArthur, Danielle M. Nash; Maccabi Health System: Varda Shalev, Gabriel Chodick; Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of a Nurse Practitioner (MASTERPLAN): Peter J. Blankestijn, Jack F.M. Wetzels, Arjan D. van Zuilen, Jan A. van den Brand; Modification of Diet in Renal Disease Study (MDRD): Andrew S. Levey, Lesley A. Inker, Mark J. Sarnak, Hocine Tighiouart; Nanjing CKD Network Cohort Study (Nanjing CKD): Haitao Zhang; NephroTest Study (NephroTest): Benedicte Stengel, Marie Metzger, Martin Flamant, Pascal Houillier, Jean-Philippe Haymann; National Renal Healthcare Program – Uruguay (NRHP-URU): Pablo G. Rios, Nelson Mazzuchi, Liliana Gadola, Verónica Lamadrid, Laura Sola; New Zealand Diabetes Cohort Study (NZDCS): John F. Collins, C. Raina Elley, Timothy Kenealy; Parcours de Soins des Personnes Agées (PSPA): Olivier Moranne, Cecile Couchoud, Cecile Vigneau; Primary-Secondary Care Partnership to Prevent Adverse Outcomes in Chronic Kidney Disease (PSP CKD): Nigel J. Brunskill, Rupert W. Major, David Shepherd, James F. Medcalf; Racial and Cardiovascular Risk Anomalies in CKD Cohort (RCAV): Csaba P. Kovesdy, Kamyar Kalantar-Zadeh, Miklos Z. Molnar, Keiichi Sumida, Praveen K. Potukuchi; Reduction of Endpoints in Non-insulin Dependent Diabetes Mellitus with the Angiotensin II Antagonist Losartan (RENAAL): Hiddo J.L. Heerspink, Dick de Zeeuw, Barry Brenner; Stockholm CREAtinine Measurements Cohort (SCREAM): Juan Jesus Carrero, Alessandro Gasparini, Abdul Rashid Qureshi, Carl-Gustaf Elinder; Second Manifestations of ARTerial Disease Study (SMART): Frank L.J. Visseren, Yolanda van der Graaf; Swedish Renal Registry CKD Cohort (SRR CKD): Marie Evans, Maria Stendahl, Staffan Schön, Mårten Segelmark, Karl-Göran Prütz; Sunnybrook Cohort: David M. Naimark, Navdeep Tangri; West of Scotland CKD Study: Patrick B. Mark, Jamie P. Traynor, Colin C. Geddes, Peter C. Thomson.• CKD Prognosis Consortium Steering Committee: Alex R. Chang, Josef Coresh (Chair), Ron T. Gansevoort, Morgan E. Grams, Anna Köttgen, Andrew S. Levey, Kunihiro Matsushita, Mark Woodward, Luxia Zhang.• CKD Prognosis Consortium Data Coordinating Center: Shoshana H. Ballew (Assistant Project Director), Jingsha Chen (Programmer), Josef Coresh (Principal Investigator), Morgan E. Grams (Director of Nephrology Initiatives), Lucia Kwak (Programmer), Kunihiro Matsushita (Director), Yingying Sang (Lead Programmer), Aditya Surapaneni (Programmer), Mark Woodward (Senior Statistician).• Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Prognosis and Optimal Management of Patients with Advanced CKD: Kai-Uwe Eckardt (Conference Co-Chair), Brenda R. Hemmelgarn (Conference Co-Chair), David C. Wheeler (KDIGO Co-Chair), Wolfgang C. Winkelmayer (KDIGO Co-Chair), John Davis (CEO), Danielle Green (Managing Director), Michael Cheung (Chief Scientific Officer), Tanya Green (Communications Director), Melissa McMahan (Programs Director)
Erratum: Grams ME, Sang Y, Ballew SH, et al, for the Chronic Kidney Disease Prognosis Consortium. Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. Kidney Int. 2018;93:1442–1451 (Kidney International (2018) 93(6) (1442–1451), (S0085253818300978) (10.1016/j.kint.2018.01.009))
No full textThe Chronic Kidney Disease (CKD) Prognosis Consortium is a collaborative author of the above-mentioned article. The CKD Prognosis Consortium investigators/collaborators are as follows: • African American Study of Kidney Disease and Hypertension (AASK): Brad Astor, Lawrence J. Appel; Canadian Study of Prediction of Death, Dialysis and Interim Cardiovascular Events (CanPREDDICT): Adeera Levin, Mila Tang, Ognjenka Djurdjev; Cleveland Clinic CKD Registry Study (CCF): Sankar D. Navaneethan, Stacey E. Jolly, Jesse D. Schold, Joseph V. Nally Jr.; Chronic Renal Impairment in Birmingham (CRIB): David C. Wheeler, Jonathan Emberson, John Townend, Martin Landray; Chronic Renal Insufficiency Cohort Study (CRIC): Harold I. Feldman, Chi-yuan Hsu, James P. Lash, Lawrence J. Appel; Chronic Renal Insufficiency Standards Implementation Study (CRISIS): Philip A. Kalra, James P. Ritchie, Raman Maharajan, Rachel J. Middleton, Donal J. O'Donoghue; German Chronic Kidney Disease Study (GCKD): Kai-Uwe Eckardt, Markus P. Schneider, Anna Köttgen, Florian Kronenberg, Barbara Bärthlein; Geisinger Health System: Alex R. Chang, Jamie A. Green, H. Lester Kirchner, Kevin Ho; Grampian Laboratory Outcomes, Morbidity and Mortality Studies – 2 (GLOMMS2): Angharad Marks, Corri Black, Gordon J. Prescott, Nick Fluck; Gonryo Study: Masaaki Nakayama, Mariko Miyazaki, Tae Yamamoto, Gen Yamada; Hong Kong CKD Studies: Angela Yee-Moon Wang, Sharon Cheung, Sharon Wong, Jessie Chu, Henry Wu; Ontario Institute for Clinical Evaluative Sciences, Provincial Kidney, Dialysis and Transplantation program (ICES KDT): Amit X. Garg, Eric McArthur, Danielle M. Nash; Maccabi Health System: Varda Shalev, Gabriel Chodick; Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of a Nurse Practitioner (MASTERPLAN): Peter J. Blankestijn, Jack F.M. Wetzels, Arjan D. van Zuilen, Jan A. van den Brand; Modification of Diet in Renal Disease Study (MDRD): Andrew S. Levey, Lesley A. Inker, Mark J. Sarnak, Hocine Tighiouart; Nanjing CKD Network Cohort Study (Nanjing CKD): Haitao Zhang; NephroTest Study (NephroTest): Benedicte Stengel, Marie Metzger, Martin Flamant, Pascal Houillier, Jean-Philippe Haymann; National Renal Healthcare Program – Uruguay (NRHP-URU): Pablo G. Rios, Nelson Mazzuchi, Liliana Gadola, Verónica Lamadrid, Laura Sola; New Zealand Diabetes Cohort Study (NZDCS): John F. Collins, C. Raina Elley, Timothy Kenealy; Parcours de Soins des Personnes Agées (PSPA): Olivier Moranne, Cecile Couchoud, Cecile Vigneau; Primary-Secondary Care Partnership to Prevent Adverse Outcomes in Chronic Kidney Disease (PSP CKD): Nigel J. Brunskill, Rupert W. Major, David Shepherd, James F. Medcalf; Racial and Cardiovascular Risk Anomalies in CKD Cohort (RCAV): Csaba P. Kovesdy, Kamyar Kalantar-Zadeh, Miklos Z. Molnar, Keiichi Sumida, Praveen K. Potukuchi; Reduction of Endpoints in Non-insulin Dependent Diabetes Mellitus with the Angiotensin II Antagonist Losartan (RENAAL): Hiddo J.L. Heerspink, Dick de Zeeuw, Barry Brenner; Stockholm CREAtinine Measurements Cohort (SCREAM): Juan Jesus Carrero, Alessandro Gasparini, Abdul Rashid Qureshi, Carl-Gustaf Elinder; Second Manifestations of ARTerial Disease Study (SMART): Frank L.J. Visseren, Yolanda van der Graaf; Swedish Renal Registry CKD Cohort (SRR CKD): Marie Evans, Maria Stendahl, Staffan Schön, Mårten Segelmark, Karl-Göran Prütz; Sunnybrook Cohort: David M. Naimark, Navdeep Tangri; West of Scotland CKD Study: Patrick B. Mark, Jamie P. Traynor, Colin C. Geddes, Peter C. Thomson.• CKD Prognosis Consortium Steering Committee: Alex R. Chang, Josef Coresh (Chair), Ron T. Gansevoort, Morgan E. Grams, Anna Köttgen, Andrew S. Levey, Kunihiro Matsushita, Mark Woodward, Luxia Zhang.• CKD Prognosis Consortium Data Coordinating Center: Shoshana H. Ballew (Assistant Project Director), Jingsha Chen (Programmer), Josef Coresh (Principal Investigator), Morgan E. Grams (Director of Nephrology Initiatives), Lucia Kwak (Programmer), Kunihiro Matsushita (Director), Yingying Sang (Lead Programmer), Aditya Surapaneni (Programmer), Mark Woodward (Senior Statistician).• Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Prognosis and Optimal Management of Patients with Advanced CKD: Kai-Uwe Eckardt (Conference Co-Chair), Brenda R. Hemmelgarn (Conference Co-Chair), David C. Wheeler (KDIGO Co-Chair), Wolfgang C. Winkelmayer (KDIGO Co-Chair), John Davis (CEO), Danielle Green (Managing Director), Michael Cheung (Chief Scientific Officer), Tanya Green (Communications Director), Melissa McMahan (Programs Director)
Prevention-focused self-regulation and aggressiveness
No full textThe present research examined the relationship between individual differences in self-regulatory mechanisms as outlined in regulatory focus theory (promotion- and prevention-focused self-regulation) and aggressiveness. Two studies revealed that the more individuals’ habitual self-regulatory orientation is dominated by a prevention-focus, the more likely they are to score high on measures of cynical hostility, reciprocity norm endorsement, and aggressiveness. An additional study involving the manipulation of perceived violation of a reciprocity norm showed that predominantly prevention-focused participants were particularly sensitive to the experience of a norm violation and reacted in a hostile and aggressive manner following the norm violation experience. Findings indicate that a prevention-focused style of self-regulation is associated with aggressiveness and suggest that endorsement of (negative) reciprocity norms and sensitivity to norm violations are relevant factors that help explain the differences in aggressiveness observed among individuals with a predominantly prevention-focused style of self-regulation
