Chemically defined cytokine-free expansion of human haematopoietic stem cells.

Haematopoietic stem cells (HSCs) are a rare cell type that reconstitute the entire blood and immune systems after transplantation and can be used as a curative cell therapy for a variety of haematological diseases1,2. However, the low number of HSCs in the body makes both biological analyses and clinical application difficult, and the limited extent to which human HSCs can be expanded ex vivo remains a substantial barrier to the wider and safer therapeutic use of HSC transplantation3. Although various reagents have been tested in attempts to stimulate the expansion of human HSCs, cytokines have long been thought to be essential for supporting HSCs ex vivo4. Here we report the establishment of a culture system that allows the long-term ex vivo expansion of human HSCs, achieved through the complete replacement of exogenous cytokines and albumin with chemical agonists and a caprolactam-based polymer. A phosphoinositide 3-kinase activator, in combination with a thrombopoietin-receptor agonist and the pyrimidoindole derivative UM171, were sufficient to stimulate the expansion of umbilical cord blood HSCs that are capable of serial engraftment in xenotransplantation assays. Ex vivo HSC expansion was further supported by split-clone transplantation assays and single-cell RNA-sequencing analysis. Our chemically defined expansion culture system will help to advance clinical HSC therapies.

Diverse mutational landscapes in human lymphocytes.

The lymphocyte genome is prone to many threats, including programmed mutation during differentiation1, antigen-driven proliferation and residency in diverse microenvironments. Here, after developing protocols for expansion of single-cell lymphocyte cultures, we sequenced whole genomes from 717 normal naive and memory B and T cells and haematopoietic stem cells. All lymphocyte subsets carried more point mutations and structural variants than haematopoietic stem cells, with higher burdens in memory cells than in naive cells, and with T cells accumulating mutations at a higher rate throughout life. Off-target effects of immunological diversification accounted for approximately half of the additional differentiation-associated mutations in lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every on-target IGHV mutation during the germinal centre reaction. Structural variation was 16-fold higher in lymphocytes than in stem cells, with around 15% of deletions being attributable to off-target recombinase-activating gene activity. DNA damage from ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory cells. The mutation burden and signatures of normal B cells were broadly similar to those seen in many B-cell cancers, suggesting that malignant transformation of lymphocytes arises from the same mutational processes that are active across normal ontogeny. The mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.

Clonal dynamics of haematopoiesis across the human lifespan.

Age-related change in human haematopoiesis causes reduced regenerative capacity1, cytopenias2, immune dysfunction3 and increased risk of blood cancer4-6, but the reason for such abrupt functional decline after 70 years of age remains unclear. Here we sequenced 3,579 genomes from single cell-derived colonies of haematopoietic cells across 10 human subjects from 0 to 81 years of age. Haematopoietic stem cells or multipotent progenitors (HSC/MPPs) accumulated a mean of 17 mutations per year after birth and lost 30 base pairs per year of telomere length. Haematopoiesis in adults less than 65 years of age was massively polyclonal, with high clonal diversity and a stable population of 20,000-200,000 HSC/MPPs contributing evenly to blood production. By contrast, haematopoiesis in individuals aged over 75 showed profoundly decreased clonal diversity. In each of the older subjects, 30-60% of haematopoiesis was accounted for by 12-18 independent clones, each contributing 1-34% of blood production. Most clones had begun their expansion before the subject was 40 years old, but only 22% had known driver mutations. Genome-wide selection analysis estimated that between 1 in 34 and 1 in 12 non-synonymous mutations were drivers, accruing at constant rates throughout life, affecting more genes than identified in blood cancers. Loss of the Y chromosome conferred selective benefits in males. Simulations of haematopoiesis, with constant stem cell population size and constant acquisition of driver mutations conferring moderate fitness benefits, entirely explained the abrupt change in clonal structure in the elderly. Rapidly decreasing clonal diversity is a universal feature of haematopoiesis in aged humans, underpinned by pervasive positive selection acting on many more genes than currently identified.

Somatic mutation landscapes at single-molecule resolution.

Somatic mutations drive the development of cancer and may contribute to ageing and other diseases1,2. Despite their importance, the difficulty of detecting mutations that are only present in single cells or small clones has limited our knowledge of somatic mutagenesis to a minority of tissues. Here, to overcome these limitations, we developed nanorate sequencing (NanoSeq), a duplex sequencing protocol with error rates of less than five errors per billion base pairs in single DNA molecules from cell populations. This rate is two orders of magnitude lower than typical somatic mutation loads, enabling the study of somatic mutations in any tissue independently of clonality. We used this single-molecule sensitivity to study somatic mutations in non-dividing cells across several tissues, comparing stem cells to differentiated cells and studying mutagenesis in the absence of cell division. Differentiated cells in blood and colon displayed remarkably similar mutation loads and signatures to their corresponding stem cells, despite mature blood cells having undergone considerably more divisions. We then characterized the mutational landscape of post-mitotic neurons and polyclonal smooth muscle, confirming that neurons accumulate somatic mutations at a constant rate throughout life without cell division, with similar rates to mitotically active tissues. Together, our results suggest that mutational processes that are independent of cell division are important contributors to somatic mutagenesis. We anticipate that the ability to reliably detect mutations in single DNA molecules could transform our understanding of somatic mutagenesis and enable non-invasive studies on large-scale cohorts.

Emerging genetic technologies informing personalized medicine in SDS and other inherited bone marrow failure disorders.

The ribosomopathy Shwachman-Diamond syndrome (SDS) is a rare autosomal recessive inherited bone marrow failure syndrome (IBMFS) caused by mutations in the Shwachman-Bodian-Diamond syndrome (SBDS) gene, that is associated with an increased risk of myeloid malignancy. Tracking how hematopoietic stem cell (HSC) clonal dynamics change over time, assessing whether somatic genetic rescue mechanisms affect these dynamics, and mapping out when leukemic driver mutations are acquired is important to understand which individuals with SDS may go on to develop leukemia. In this review, we will discuss how new technologies that allow researchers to map mutations at the level of single HSC clones are generating important insights into genetic rescue mechanisms and their relative risk for driving evolution to leukemia, and how these data can inform the future development of personalized medicine approaches in SDS and other IBMFSs.

Lessons from early life: understanding development to expand stem cells and treat cancers.

Haematopoietic stem cell (HSC) self-renewal is a process that is essential for the development and homeostasis of the blood system. Self-renewal expansion divisions, which create two daughter HSCs from a single parent HSC, can be harnessed to create large numbers of HSCs for a wide range of cell and gene therapies, but the same process is also a driver of the abnormal expansion of HSCs in diseases such as cancer. Although HSCs are first produced during early embryonic development, the key stage and location where they undergo maximal expansion is in the foetal liver, making this tissue a rich source of data for deciphering the molecules driving HSC self-renewal. Another equally interesting stage occurs post-birth, several weeks after HSCs have migrated to the bone marrow, when HSCs undergo a developmental switch and adopt a more dormant state. Characterising these transition points during development is key, both for understanding the evolution of haematological malignancies and for developing methods to promote HSC expansion. In this Spotlight article, we provide an overview of some of the key insights that studying HSC development have brought to the fields of HSC expansion and translational medicine, many of which set the stage for the next big breakthroughs in the field.

Resolving the hematopoietic stem cell state by linking functional and molecular assays.

One of the most challenging aspects of stem cell research is the reliance on retrospective assays for ascribing function. This is especially problematic for hematopoietic stem cell (HSC) research in which the current functional assay that formally establishes its HSC identity involves long-term serial transplantation assays that necessitate the destruction of the initial cell state many months before knowing that it was, in fact, an HSC. In combination with the explosion of equally destructive single-cell molecular assays, the paradox facing researchers is how to determine the molecular state of a functional HSC when you cannot concomitantly assess its functional and molecular properties. In this review, we will give a historical overview of the functional and molecular assays in the field, identify new tools that combine molecular and functional readouts in populations of HSCs, and imagine the next generation of computational and molecular profiling tools that may help us better link cell function with molecular state.

Recommendations for empowering early career researchers to improve research culture and practice.

Early career researchers (ECRs) are important stakeholders leading efforts to catalyze systemic change in research culture and practice. Here, we summarize the outputs from a virtual unconventional conference (unconference), which brought together 54 invited experts from 20 countries with extensive experience in ECR initiatives designed to improve the culture and practice of science. Together, we drafted 2 sets of recommendations for (1) ECRs directly involved in initiatives or activities to change research culture and practice; and (2) stakeholders who wish to support ECRs in these efforts. Importantly, these points apply to ECRs working to promote change on a systemic level, not only those improving aspects of their own work. In both sets of recommendations, we underline the importance of incentivizing and providing time and resources for systems-level science improvement activities, including ECRs in organizational decision-making processes, and working to dismantle structural barriers to participation for marginalized groups. We further highlight obstacles that ECRs face when working to promote reform, as well as proposed solutions and examples of current best practices. The abstract and recommendations for stakeholders are available in Dutch, German, Greek (abstract only), Italian, Japanese, Polish, Portuguese, Spanish, and Serbian.

The clinical effectiveness of Fidaxomicin compared to Vancomycin in the treatment of Clostridioides difficile infection, a single center real-world experience.

BACKGROUND: The use of fidaxomicin is recommended as first line therapy for all patients with Clostridioides difficile infection (CDI). However, real-world studies have shown conflicting evidence of superiority. METHODS: We conducted a retrospective single center study of patients diagnosed with CDI between 2011-2021. A primary composite outcome of clinical failure, 30-day relapse or CDI-related death was used. A multivariable cause specific Cox proportional hazards model was used to evaluate fidaxomicin compared to vancomycin in preventing the composite outcome. A separate model was fit on a subset of patients with C. difficile ribotypes adjusting for ribotype. RESULTS: There were 598 patients included, of whom 84 received fidaxomicin. The primary outcome occurred in 8 (9.5%) in the fidaxomicin group compared to 111 (21.6%) in the vancomycin group. The adjusted multivariable model showed fidaxomicin was associated with 63% reduction in the risk of the composite outcome compared to vancomycin (HR = 0.37, 95% CI 0.17-0.80). In the 337 patients with ribotype data after adjusting for ribotype 027, the results showing superiority of fidaxomicin were maintained (HR = 0.19, 95% CI 0.05-0.77). CONCLUSION: In the treatment of CDI, we showed that real-world use of fidaxomicin is associated with lower risk of a composite endpoint of treatment failure.

STAT1 is essential for HSC function and maintains MHCIIhi stem cells that resist myeloablation and neoplastic expansion.

Adult hematopoietic stem cells (HSCs) are predominantly quiescent and can be activated in response to acute stress such as infection or cytotoxic insults. STAT1 is a pivotal downstream mediator of interferon (IFN) signaling and is required for IFN-induced HSC proliferation, but little is known about the role of STAT1 in regulating homeostatic hematopoietic stem/progenitor cells (HSPCs). Here, we show that loss of STAT1 altered the steady state HSPC landscape, impaired HSC function in transplantation assays, delayed blood cell regeneration following myeloablation, and disrupted molecular programs that protect HSCs, including control of quiescence. Our results also reveal STAT1-dependent functional HSC heterogeneity. A previously unrecognized subset of homeostatic HSCs with elevated major histocompatibility complex class II (MHCII) expression (MHCIIhi) displayed molecular features of reduced cycling and apoptosis and was refractory to 5-fluorouracil-induced myeloablation. Conversely, MHCIIlo HSCs displayed increased megakaryocytic potential and were preferentially expanded in CALR mutant mice with thrombocytosis. Similar to mice, high MHCII expression is a feature of human HSCs residing in a deeper quiescent state. Our results therefore position STAT1 at the interface of stem cell heterogeneity and the interplay between stem cells and the adaptive immune system, areas of broad interest in the wider stem cell field.

Identification and characterization of in vitro expanded hematopoietic stem cells.

Hematopoietic stem cells (HSCs) cultured outside the body are the fundamental component of a wide range of cellular and gene therapies. Recent efforts have achieved > 200-fold expansion of functional HSCs, but their molecular characterization has not been possible since the majority of cells are non-HSCs and single cell-initiated cultures have substantial clone-to-clone variability. Using the Fgd5 reporter mouse in combination with the EPCR surface marker, we report exclusive identification of HSCs from non-HSCs in expansion cultures. By directly linking single-clone functional transplantation data with single-clone gene expression profiling, we show that the molecular profile of expanded HSCs is similar to proliferating fetal HSCs and reveals a gene expression signature, including Esam, Prdm16, Fstl1, and Palld, that can identify functional HSCs from multiple cellular states. This "repopulation signature" (RepopSig) also enriches for HSCs in human datasets. Together, these findings demonstrate the power of integrating functional and molecular datasets to better derive meaningful gene signatures and opens the opportunity for a wide range of functional screening and molecular experiments previously not possible due to limited HSC numbers.

Population dynamics of normal human blood inferred from somatic mutations.

Haematopoietic stem cells drive blood production, but their population size and lifetime dynamics have not been quantified directly in humans. Here we identified 129,582 spontaneous, genome-wide somatic mutations in 140 single-cell-derived haematopoietic stem and progenitor colonies from a healthy 59-year-old man and applied population-genetics approaches to reconstruct clonal dynamics. Cell divisions from early embryogenesis were evident in the phylogenetic tree; all blood cells were derived from a common ancestor that preceded gastrulation. The size of the stem cell population grew steadily in early life, reaching a stable plateau by adolescence. We estimate the numbers of haematopoietic stem cells that are actively making white blood cells at any one time to be in the range of 50,000-200,000. We observed adult haematopoietic stem cell clones that generate multilineage outputs, including granulocytes and B lymphocytes. Harnessing naturally occurring mutations to report the clonal architecture of an organ enables the high-resolution reconstruction of somatic cell dynamics in humans.

First Evidence of Cutaneous Remodelling Induced by Synchronized Radiofrequency Aided by High-Intensity Facial Muscle Stimulation: Porcine Animal Model.

BACKGROUND: The quality of one's facial appearance diminishes with aging as skin and underlying soft tissues deteriorate. Connective tissue and musculofascial degeneration leads to skin laxity and wrinkles developing. OBJECTIVE: To evaluate the effects of synchronized radiofrequency with high intensity facial stimulation technology on dermal collagen and elastin fibers in a porcine model. MATERIALS AND METHODS: Eight sows were divided into Active (N = 6) and Control (N = 2) groups. Synchronized radiofrequency and high intensity facial stimulation were delivered to the ventrolateral abdomen. The Active group received four 20-minute treatments, once a week. Control group was untreated. Skin biopsy sample were histologically analyzed for connective tissue changes pre- and post-treatment. Data were analyzed statistically (α = 0.05). RESULTS: In the Active group: the collagen-occupied area at baseline was 1.12 ± 0.09 × 106 µm 2 and increased by +19.6% ( p < .001) at 1-month and by +26.3% ( p < .001) 2 months post-treatment; elastin-occupied area at baseline was 0.11 ± 0.03 × 106 µm 2 and increased by +75.9% ( p < .001) at 1-month and +110.8% ( p < .001) at 2-months follow-up. No significant changes ( p > .05) found in the Control samples. CONCLUSION: Collagen and elastin fiber content increased significantly after treatments. Connective tissue in the treatment area was denser up to 2-months post-treatment.

Treatment effect modification due to comorbidity: Individual participant data meta-analyses of 120 randomised controlled trials.

BACKGROUND: People with comorbidities are underrepresented in clinical trials. Empirical estimates of treatment effect modification by comorbidity are lacking, leading to uncertainty in treatment recommendations. We aimed to produce estimates of treatment effect modification by comorbidity using individual participant data (IPD). METHODS AND FINDINGS: We obtained IPD for 120 industry-sponsored phase 3/4 trials across 22 index conditions (n = 128,331). Trials had to be registered between 1990 and 2017 and have recruited ≥300 people. Included trials were multicentre and international. For each index condition, we analysed the outcome most frequently reported in the included trials. We performed a two-stage IPD meta-analysis to estimate modification of treatment effect by comorbidity. First, for each trial, we modelled the interaction between comorbidity and treatment arm adjusted for age and sex. Second, for each treatment within each index condition, we meta-analysed the comorbidity-treatment interaction terms from each trial. We estimated the effect of comorbidity measured in 3 ways: (i) the number of comorbidities (in addition to the index condition); (ii) presence or absence of the 6 commonest comorbid diseases for each index condition; and (iii) using continuous markers of underlying conditions (e.g., estimated glomerular filtration rate (eGFR)). Treatment effects were modelled on the usual scale for the type of outcome (absolute scale for numerical outcomes, relative scale for binary outcomes). Mean age in the trials ranged from 37.1 (allergic rhinitis trials) to 73.0 (dementia trials) and percentage of male participants range from 4.4% (osteoporosis trials) to 100% (benign prostatic hypertrophy trials). The percentage of participants with 3 or more comorbidities ranged from 2.3% (allergic rhinitis trials) to 57% (systemic lupus erythematosus trials). We found no evidence of modification of treatment efficacy by comorbidity, for any of the 3 measures of comorbidity. This was the case for 20 conditions for which the outcome variable was continuous (e.g., change in glycosylated haemoglobin in diabetes) and for 3 conditions in which the outcomes were discrete events (e.g., number of headaches in migraine). Although all were null, estimates of treatment effect modification were more precise in some cases (e.g., sodium-glucose co-transporter-2 (SGLT2) inhibitors for type 2 diabetes-interaction term for comorbidity count 0.004, 95% CI -0.01 to 0.02) while for others credible intervals were wide (e.g., corticosteroids for asthma-interaction term -0.22, 95% CI -1.07 to 0.54). The main limitation is that these trials were not designed or powered to assess variation in treatment effect by comorbidity, and relatively few trial participants had >3 comorbidities. CONCLUSIONS: Assessments of treatment effect modification rarely consider comorbidity. Our findings demonstrate that for trials included in this analysis, there was no empirical evidence of treatment effect modification by comorbidity. The standard assumption used in evidence syntheses is that efficacy is constant across subgroups, although this is often criticised. Our findings suggest that for modest levels of comorbidities, this assumption is reasonable. Thus, trial efficacy findings can be combined with data on natural history and competing risks to assess the likely overall benefit of treatments in the context of comorbidity.

Comorbidity and health-related quality of life in people with a chronic medical condition in randomised clinical trials: An individual participant data meta-analysis.

BACKGROUND: Health-related quality of life metrics evaluate treatments in ways that matter to patients, so are often included in randomised clinical trials (hereafter trials). Multimorbidity, where individuals have 2 or more conditions, is negatively associated with quality of life. However, whether multimorbidity predicts change over time or modifies treatment effects for quality of life is unknown. Therefore, clinicians and guideline developers are uncertain about the applicability of trial findings to people with multimorbidity. We examined whether comorbidity count (higher counts indicating greater multimorbidity) (i) is associated with quality of life at baseline; (ii) predicts change in quality of life over time; and/or (iii) modifies treatment effects on quality of life. METHODS AND FINDINGS: Included trials were registered on the United States trials registry for selected index medical conditions and drug classes, phase 2/3, 3 or 4, had ≥300 participants, a nonrestrictive upper age limit, and were available on 1 of 2 trial repositories on 21 November 2016 and 18 May 2018, respectively. Of 124 meeting these criteria, 56 trials (33,421 participants, 16 index conditions, and 23 drug classes) collected a generic quality of life outcome measure (35 EuroQol-5 dimension (EQ-5D), 31 36-item short form survey (SF-36) with 10 collecting both). Blinding and completeness of follow up were examined for each trial. Using trials where individual participant data (IPD) was available from 2 repositories, a comorbidity count was calculated from medical history and/or prescriptions data. Linear regressions were fitted for the association between comorbidity count and (i) quality of life at baseline; (ii) change in quality of life during trial follow up; and (iii) treatment effects on quality of life. These results were then combined in Bayesian linear models. Posterior samples were summarised via the mean, 2.5th and 97.5th percentiles as credible intervals (95% CI) and via the proportion with values less than 0 as the probability (PBayes) of a negative association. All results are in standardised units (obtained by dividing the EQ-5D/SF-36 estimates by published population standard deviations). Per additional comorbidity, adjusting for age and sex, across all index conditions and treatment comparisons, comorbidity count was associated with lower quality of life at baseline and with a decline in quality of life over time (EQ-5D -0.02 [95% CI -0.03 to -0.01], PBayes > 0.999). Associations were similar, but with wider 95% CIs crossing the null for SF-36-PCS and SF-36-MCS (-0.05 [-0.10 to 0.01], PBayes = 0.956 and -0.05 [-0.10 to 0.01], PBayes = 0.966, respectively). Importantly, there was no evidence of any interaction between comorbidity count and treatment efficacy for either EQ-5D or SF-36 (EQ-5D -0.0035 [95% CI -0.0153 to -0.0065], PBayes = 0.746; SF-36-MCS (-0.0111 [95% CI -0.0647 to 0.0416], PBayes = 0.70 and SF-36-PCS -0.0092 [95% CI -0.0758 to 0.0476], PBayes = 0.631. CONCLUSIONS: Treatment effects on quality of life did not differ by multimorbidity (measured via a comorbidity count) at baseline-for the medical conditions studied, types and severity of comorbidities and level of quality of life at baseline, suggesting that evidence from clinical trials is likely to be applicable to settings with (at least modestly) higher levels of comorbidity. TRIAL REGISTRATION: A prespecified protocol was registered on PROSPERO (CRD42018048202).

Development of Parkinson Disease and Its Relationship with Incidentally Discovered White Matter Disease and Covert Brain Infarction in a Real-World Cohort.

OBJECTIVE: This study aimed to examine the relationship between covert cerebrovascular disease, comprised of covert brain infarction and white matter disease, discovered incidentally in routine care, and subsequent Parkinson disease. METHODS: Patients were ≥50 years and received neuroimaging for non-stroke indications in the Kaiser Permanente Southern California system from 2009 to 2019. Natural language processing identified incidentally discovered covert brain infarction and white matter disease and classified white matter disease severity. The Parkinson disease outcome was defined as 2 ICD diagnosis codes. RESULTS: 230,062 patients were included (median follow-up 3.72 years). A total of 1,941 Parkinson disease cases were identified (median time-to-event 2.35 years). Natural language processing identified covert cerebrovascular disease in 70,592 (30.7%) patients, 10,622 (4.6%) with covert brain infarction and 65,814 (28.6%) with white matter disease. After adjustment for known risk factors, white matter disease was associated with Parkinson disease (hazard ratio 1.67 [95%CI, 1.44, 1.93] for patients <70 years and 1.33 [1.18, 1.50] for those ≥70 years). Greater severity of white matter disease was associated with increased incidence of Parkinson disease(/1,000 person-years), from 1.52 (1.43, 1.61) in patients without white matter disease to 4.90 (3.86, 6.13) in those with severe disease. Findings were robust when more specific definitions of Parkinson disease were used. Covert brain infarction was not associated with Parkinson disease (adjusted hazard ratio = 1.05 [0.88, 1.24]). INTERPRETATION: Incidentally discovered white matter disease was associated with subsequent Parkinson disease, an association strengthened with younger age and increased white matter disease severity. Incidentally discovered covert brain infarction did not appear to be associated with subsequent Parkinson disease. ANN NEUROL 2022;92:620-630.

Assessing heterogeneity of treatment effect in multiple sclerosis trials.

Multiple sclerosis (MS) is heterogeneous with respect to outcomes, and evaluating possible heterogeneity of treatment effect (HTE) is of high interest. HTE is non-random variation in the magnitude of a treatment effect on a clinical outcome across levels of a covariate (i.e. a patient attribute or set of attributes). Multiple statistical techniques can evaluate HTE. The simplest but most bias-prone is conventional one variable-at-a-time subgroup analysis. Recently, multivariable predictive approaches have been promoted to provide more patient-centered results, by accounting for multiple relevant attributes simultaneously. We review approaches used to estimate HTE in clinical trials of MS.

Stratifying Future Stroke Risk with Incidentally Discovered White Matter Disease Severity and Covert Brain Infarct Site.

BACKGROUND: Covert cerebrovascular disease (CCD) includes white matter disease (WMD) and covert brain infarction (CBI). Incidentally discovered CCD is associated with increased risk of subsequent symptomatic stroke. However, it is unknown whether the severity of WMD or the location of CBI predicts risk. OBJECTIVES: The aim of this study was to examine the association of incidentally discovered WMD severity and CBI location with risk of subsequent symptomatic stroke. METHOD: This retrospective cohort study includes patients aged ≥50 years old in the Kaiser Permanente Southern California health system who received neuroimaging for a nonstroke indication between 2009 and 2019. Incidental CBI and WMD were identified via natural language processing of the neuroimage report, and WMD severity was classified into grades. RESULTS: A total of 261,960 patients received neuroimaging; 78,555 patients (30.0%) were identified to have incidental WMD and 12,857 patients (4.9%) to have incidental CBI. Increasing WMD severity is associated with an increased incidence rate of future stroke. However, the stroke incidence rate in CT-identified WMD is higher at each level of severity compared to rates in MRI-identified WMD. Patients with mild WMD via CT have a stroke incidence rate of 24.9 per 1,000 person-years, similar to that of patients with severe WMD via MRI. Among incidentally discovered CBI patients with a determined CBI location, 97.9% are subcortical rather than cortical infarcts. CBI confers a similar risk of future stroke, whether cortical or subcortical or whether MRI- or CT-detected. CONCLUSIONS: Increasing severity of incidental WMD is associated with an increased risk of future symptomatic stroke, dependent on the imaging modality. Subcortical and cortical CBI conferred similar risks.

Stratifying future stroke risk with incidentally-discovered white matter disease severity and covert brain infarct site.

BACKGROUND: Covert cerebrovascular disease (CCD) includes white matter disease (WMD) and covert brain infarction (CBI). Incidentally-discovered CCD is associated with increased risk of subsequent symptomatic stroke. However, it is unknown whether the severity of WMD or the location of CBI predicts risk. OBJECTIVES: To examine the association of incidentally-discovered WMD severity and CBI location with risk of subsequent symptomatic stroke. METHOD: This retrospective cohort study includes patients 50 years old in the Kaiser Permanente Southern California health system who received neuroimaging for a non-stroke indication between 2009-2019. Incidental CBI and WMD were identified via natural language processing of the neuroimage report, and WMD severity was classified into grades. RESULTS: 261,960 patients received neuroimaging; 78,555 (30.0%) were identified to have incidental WMD, and 12,857 (4.9%) to have incidental CBI. Increasing WMD severity is associated with increased incidence rate of future stroke. However, the stroke incidence rate in CT-identified WMD is higher at each level of severity compared to rates in MRI-identified WMD. Patients with mild WMD via CT have a stroke incidence rate of 24.9 per 1,000 person-years, similar to that of patients with severe WMD via MRI. Among incidentally-discovered CBI patients with a determined CBI location, 97.9% are subcortical rather than cortical infarcts. CBI confers a similar risk of future stroke, whether cortical or subcortical, or whether MRI- or CT-detected. CONCLUSIONS: Increasing severity of incidental WMD is associated with an increased risk of future symptomatic stroke, dependent on the imaging modality. Subcortical and cortical CBI conferred similar risks.

Estimating individualized treatment effects from randomized controlled trials: a simulation study to compare risk-based approaches.

BACKGROUND: Baseline outcome risk can be an important determinant of absolute treatment benefit and has been used in guidelines for "personalizing" medical decisions. We compared easily applicable risk-based methods for optimal prediction of individualized treatment effects. METHODS: We simulated RCT data using diverse assumptions for the average treatment effect, a baseline prognostic index of risk, the shape of its interaction with treatment (none, linear, quadratic or non-monotonic), and the magnitude of treatment-related harms (none or constant independent of the prognostic index). We predicted absolute benefit using: models with a constant relative treatment effect; stratification in quarters of the prognostic index; models including a linear interaction of treatment with the prognostic index; models including an interaction of treatment with a restricted cubic spline transformation of the prognostic index; an adaptive approach using Akaike's Information Criterion. We evaluated predictive performance using root mean squared error and measures of discrimination and calibration for benefit. RESULTS: The linear-interaction model displayed optimal or close-to-optimal performance across many simulation scenarios with moderate sample size (N = 4,250; ~ 785 events). The restricted cubic splines model was optimal for strong non-linear deviations from a constant treatment effect, particularly when sample size was larger (N = 17,000). The adaptive approach also required larger sample sizes. These findings were illustrated in the GUSTO-I trial. CONCLUSIONS: An interaction between baseline risk and treatment assignment should be considered to improve treatment effect predictions.