Jane Lange
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View article: Clinical Significance of a Multicancer Screening Trial With Stage-Based End Points
Clinical Significance of a Multicancer Screening Trial With Stage-Based End Points Open
Importance The first randomized screening trial of a multicancer early detection test is ongoing, with the primary end point being the incidence of late-stage cancer. The unprecedented use of a stage-based end point and short 3-year follow…
View article: The power of quantum circuits in sampling
The power of quantum circuits in sampling Open
We give new evidence that quantum circuits are substantially more powerful than classical circuits. We show, relative to a random oracle, that polynomial-size quantum circuits can sample distributions that subexponential-size classical cir…
View article: Estimating the Opportunity for Early Detection of Ovarian Cancer Using Individual-Patient Data from a Large Randomized Controlled Trial
Estimating the Opportunity for Early Detection of Ovarian Cancer Using Individual-Patient Data from a Large Randomized Controlled Trial Open
Background: The UK Collaborative Trial of Ovarian Cancer Screening did not detect a reduction in ovarian cancer mortality with either multimodal screening (MMS) or transvaginal ultrasound screening (USS) compared with no screening. The tri…
View article: Data from Sensitivity Measures in Studies of Cancer Early Detection Biomarkers
Data from Sensitivity Measures in Studies of Cancer Early Detection Biomarkers Open
Background:The sensitivity of a cancer screening biomarker to detect prevalent preclinical cancer drives screening benefit. Studies estimate sensitivity at different points in the biomarker development process. We examine how closely these…
View article: Sup Materials and Methods from Sensitivity Measures in Studies of Cancer Early Detection Biomarkers
Sup Materials and Methods from Sensitivity Measures in Studies of Cancer Early Detection Biomarkers Open
Supplementary Materials and Methods
View article: Sensitivity Measures in Studies of Cancer Early Detection Biomarkers
Sensitivity Measures in Studies of Cancer Early Detection Biomarkers Open
Background: The sensitivity of a cancer screening biomarker to detect prevalent preclinical cancer drives screening benefit. Studies estimate sensitivity at different points in the biomarker development process. We examine how closely thes…
View article: Cancer incidence and competing mortality risk following 15 presenting symptoms in primary care: a population-based cohort study using electronic healthcare records
Cancer incidence and competing mortality risk following 15 presenting symptoms in primary care: a population-based cohort study using electronic healthcare records Open
· Objectives Assessment of age, sex and smoking-specific risk of cancer diagnosis and non-cancer mortality following primary care consultation for 15 new-onset symptoms. Methods and analysis Data on patients aged 30–99 in 2007–2017 were ex…
View article: Predicting quantum channels over general product distributions
Predicting quantum channels over general product distributions Open
We investigate the problem of predicting the output behavior of unknown quantum channels. Given query access to an $n$-qubit channel $E$ and an observable $O$, we aim to learn the mapping \begin{equation*} ρ\mapsto \mathrm{Tr}(O E[ρ]) \end…
View article: Breast density and risk of breast cancer: masking and detection bias
Breast density and risk of breast cancer: masking and detection bias Open
Breast density is associated with risk of breast cancer (BC) diagnosis, affecting risk prediction tools and patient notification policies. Density affects mammography sensitivity and may influence screening intensity. Therefore, the observ…
View article: A Scaled Proteomic Discovery Study for Prostate Cancer Diagnostic Markers Using ProteographTM and Trapped Ion Mobility Mass Spectrometry
A Scaled Proteomic Discovery Study for Prostate Cancer Diagnostic Markers Using ProteographTM and Trapped Ion Mobility Mass Spectrometry Open
There is a significant unmet need for clinical reflex tests that increase the specificity of prostate-specific antigen blood testing, the longstanding but imperfect tool for prostate cancer diagnosis. Towards this endpoint, we present the …
View article: Supplementary Table S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S4: Overall and cancer-specific relative reductions in late-stage incidence for MCED trials with varying numbers of annual screens and with specified overall mean sojourn time (OMST) and late-stage mean sojourn time (LM…
View article: Supplementary Figure S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S1: Two-stage progressive natural history model with hypoexponential preclinical onset distribution.
View article: Supplementary Table S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S2: Targeted cancers in MCED trial and test sensitivities in clinically detected patients.
View article: Supplementary Figure S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S2: Early- and late-stage solid cancer incidence rates by age observed in the Surveillance, Epidemiology, and End Results program in 2006-2015 (both sexes) and corresponding projections from models fit under the pairs …
View article: Supplementary Methods S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Methods S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Methods S1: used for Projecting the impact of multi-cancer early detection on late-stage incidence using multi-state disease modeling.
View article: Supplementary Figure S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S2: Early- and late-stage solid cancer incidence rates by age observed in the Surveillance, Epidemiology, and End Results program in 2006-2015 (both sexes) and corresponding projections from models fit under the pairs …
View article: Supplementary Table S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S4: Overall and cancer-specific relative reductions in late-stage incidence for MCED trials with varying numbers of annual screens and with specified overall mean sojourn time (OMST) and late-stage mean sojourn time (LM…
View article: Supplementary Table S5 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S5 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S5: Overall and cancer-specific relative reductions in late-stage incidence for MCED trials with varying numbers of annual screens and with specified overall mean sojourn time (OMST) and late-stage mean sojourn time (LM…
View article: Supplementary Figure S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S4: Scatterplot of early-stage mean sojourn time (EMST) and ratio of observed early-stage incidence to late-stage incidence at age 65 assuming an overall sojourn time of 4 years and late-stage mean sojourn time of 1 ye…
View article: Supplementary Table S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S3: Early mean sojourn time (EMST) by cancer site corresponding to specified overall mean sojourn times (OMST) and late mean sojourn times (LMST)
View article: Supplementary Methods S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Methods S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Methods S1: used for Projecting the impact of multi-cancer early detection on late-stage incidence using multi-state disease modeling.
View article: Supplementary Table S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S1: Sources of inputs for the lung cancer validation.
View article: Supplementary Figure S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S1: Two-stage progressive natural history model with hypoexponential preclinical onset distribution.
View article: Supplementary Table S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S1 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S1: Sources of inputs for the lung cancer validation.
View article: Supplementary Figure S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S3: Early- and late-stage solid cancer incidence rates by age observed in the Surveillance, Epidemiology, and End Results program in 2006-2015 (female only) and corresponding projections from models fit under the pairs…
View article: Supplementary Table S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S2 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S2: Targeted cancers in MCED trial and test sensitivities in clinically detected patients.
View article: Supplementary Figure S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S3: Early- and late-stage solid cancer incidence rates by age observed in the Surveillance, Epidemiology, and End Results program in 2006-2015 (female only) and corresponding projections from models fit under the pairs…
View article: Supplementary Table S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Table S3 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Table S3: Early mean sojourn time (EMST) by cancer site corresponding to specified overall mean sojourn times (OMST) and late mean sojourn times (LMST)
View article: Data from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Data from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Background:Downstaging—reduction in late-stage incidence—has been proposed as an endpoint in randomized trials of multi-cancer early detection (MCED) tests. How downstaging depends on test performance and follow-up has been studied for som…
View article: Supplementary Figure S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling
Supplementary Figure S4 from Projecting the Impact of Multi-Cancer Early Detection on Late-Stage Incidence Using Multi-State Disease Modeling Open
Supplementary Figure S4: Scatterplot of early-stage mean sojourn time (EMST) and ratio of observed early-stage incidence to late-stage incidence at age 65 assuming an overall sojourn time of 4 years and late-stage mean sojourn time of 1 ye…