Survival analysis with delayed entry in selected families with application to human longevity

In the field of aging research, family-based sampling study designs are commonly used to study the lifespans of long-lived family members. However, the specific sampling procedure should be carefully taken into account in order to avoid biases. This work is motivated by the Leiden Longevity Study, a family-based cohort of long-lived siblings. Families were invited to participate in the study if at least two siblings were ‘long-lived’, where ‘long-lived’ meant being older than 89 years for men or older than 91 years for women. As a result, more than 400 families were included in the study and followed for around 10 years. For estimation of marker-specific survival probabilities and correlations among life times of family members, delayed entry due to outcome-dependent sampling mechanisms has to be taken into account. We consider shared frailty models to model left-truncated correlated survival data. The treatment of left truncation in shared frailty models is still an open issue and the literature on this topic is scarce. We show that the current approaches provide, in general, biased estimates and we propose a new method to tackle this selection problem by applying a correction on the likelihood estimation by means of inverse probability weighting at the family level

Sequential double cross-validation for assessment of added predictive ability in high-dimensional omic applications

Enriching existing predictive models with new biomolecular markers is an important task in the new multi-omic era. Clinical studies increasingly include new sets of omic measurements which may prove their added value in terms of predictive performance. We introduce a two-step approach for the assessment of the added predictive ability of omic predictors, based on sequential double cross-validation and regularized regression models. We propose several performance indices to summarize the two-stage prediction procedure and a permutation test to formally assess the added predictive value of a second omic set of predictors over a primary omic source. The performance of the test is investigated through simulations. We illustrate the new method through the systematic assessment and comparison of the performance of transcriptomics and metabolomics sources in the prediction of body mass index (BMI) using longitudinal data from the Dietary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) study, a population-based cohort from Finland

Improved selection of participants in genetic longevity studies: family scores revisited

Background: Although human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data.Methods: We discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN).Results: Empirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score .Conclusions: Model-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.Development and application of statistical models for medical scientific researc

Effects of Family History on Relative and Absolute Risks for Colorectal Cancer: A Systematic Review and Meta-Analysis

Analysis and support of clinical decision makin

Universal Immunohistochemistry for Lynch Syndrome: A Systematic Review and Meta-analysis of 58,580 Colorectal Carcinomas

BACKGROUND & AIMS: Lynch syndrome is a form of hereditary colorectal cancer (CRC) caused by pathogenic germline variants (PV) in DNA mismatch repair (MMR) genes. Currently, many Western countries perform universal immunohistochemistry testing on CRC to increase the identification of Lynch syndrome patients and their relatives. For a clear understanding of health benefits and costs, data on its outcomes are required: proportions of Lynch syndrome, sporadic MMR-deficient (MMRd) cases, and unexplained MMRd cases.METHODS: Ovid Medline, Embase, and Cochrane CENTRAL were searched for studies reporting on universal MMR immunohistochemistry, followed by MMR germline analysis, until March 20, 2020. Proportions were calculated, subgroup analyses were performed based on age and diagnostics used, and random effects meta-analyses were conducted. Quality was assessed using the Joanna Briggs Critical Appraisal Tool for Prevalence Studies.RESULTS: Of 2723 identified articles, 56 studies covering 58,580 CRCs were included. In 6.22% (95% CI, 5.08%-7.61%; I-2 = 96%) MMRd was identified. MMR germline PV was present in 2.00% (95% CI, 1.59%-2.50%; I-2 = 92%), ranging from 1.80% to 7.27% based on completeness of diagnostics and age restriction. Immunohistochemistry outcomes were missing in 11.81%, and germline testing was performed in 76.30% of eligible patients. In 7 studies, including 6848 CRCs completing all diagnostic stages, germline PV and biallelic somatic MMR inactivation were found in 3.01% and 1.75%, respectively; 0.61% remained unexplained MMRd.CONCLUSIONS: Age, completeness, and type of diagnostics affect the percentage of MMR PV and unexplained MMRd percentages. Complete diagnostics explain almost all MMRd CRCs, reducing the amount of subsequent multigene panel testing. This contributes to optimizing testing and surveillance in MMRd CRC patients and relatives.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Estimating the age at onset distribution of the asymptomatic stage of a genetic disease based on pedigree data

Information on the age at onset distribution of the asymptomatic stage of a disease can be of paramount importance in early detection and timely management of that disease. However, accurately estimating this distribution is challenging, because the asymptomatic stage is difficult to recognize for the patient and is often detected as an incidental finding or in case of recommended screening; the age at onset is often interval-censored. In this paper, we propose a method for the estimation of the age at onset distribution of the asymptomatic stage of a genetic disease based on ascertained pedigree data that take into account the way the data are ascertained to overcome selection bias. Simulation studies show that the estimates seem to be asymptotically unbiased. Our work is motivated by the analysis of data on facioscapulohumeral muscular dystrophy, a genetic muscle disorder. In our application, carriers of the genetic causal variant are identified through genetic screening of the relatives of symptomatic carriers and their disease status is determined by a medical examination. The estimates reveal an early age at onset of the asymptomatic stage of facioscapulohumeral muscular dystrophy

A Short-form version of the Boston Naming Test for language screening in Dementia in a bilingual rural community in Galicia (Spain)

Background: Aphasia, one of the core symptoms of cortical dementia, is routinely evaluated using graded naming tests like the Boston Naming Test (BNT). However, the application of this 60-item test is time-consuming and shortened versions have been devised for screening. The hypothesis of this research is that a specifically designed shortened version of the BNT could replace the original 60-item BNT as part of a mini-battery for screening for dementia. The objective of this study was to design a short version of the BNT for a rural population in Galicia (Spain). Methods: A clinic group of 102 patients including 43 with dementia was recruited along with 78 healthy volunteers. The clinic and control groups were scored on the Spanish version of the Mini-mental State Examination (MMSE) and BNT. In addition, the clinic group was tested with standard neuropsychological instruments and underwent brain investigations and routine neurological examination. BNT items with specificity and sensitivity above 0.5 were selected to compose a short battery of 11 pictures named BNTOu11. ANOVA and mean comparisons were made for MMSE and BNT versions. Receiver operating characteristics (ROC) curves and internal consistency were calculated. Results: Areas under ROC curves (AUC) did not show statistically significant differences; therefore BNTOu11's AUC (0.814) was similar to the 60-item BNT versions (0.785 and 0.779), to the short versions from Argentina (0.772) and Andalusia (0.799) and to the Spanish MMSE (0.866). BNTOu11 had higher internal consistency than the other short versions. Conclusions: BNTOu11 is a useful and time-saving method as part of a battery for screening for dementia in a psychogeriatric outpatient unit.Peer Reviewe

The Hold me Tight Program for Couples Facing Huntington's Disease

Background: A positive predictive genetic test for Huntington's disease (HD) can be a life-changing event for both carriers and their partners, leading to lower wellbeing and increasing the risk for separation and divorce. The 'Hold me Tight' program (HmT), based on emotionally focused couples' therapy, aims at strengthening the couple bond by targeting attachment needs.Objective: This study investigates whether the HmT program helps couples strengthen their relationship, as an investment in a future where the disease will affect life in many ways.Methods: In a multiple baseline design using three baselines of varying length, 15 couples of presymptomatic HD-carriers and their partners were included. In three consecutive groups, couples underwent the intervention (an adapted version of the 8-session HmT program) in four weekly sessions and completed self-report questionnaires throughout the study period of 19 weeks (17 measurements). Attachment style was assessed at baseline, resilience at baseline and at the end of the follow-up, while relationship satisfaction and wellbeing were measured weekly. A multi-level model was applied to the data.Results: Over the course of the study, wellbeing and relationship satisfaction significantly improved; resilience, however, did not. Furthermore, all three outcome measures were moderated by attachment style, with more securely attached individuals showing better outcomes.Conclusion: HmT improved wellbeing and relationship satisfaction of couples facing HD. Due to these improvements and high patient acceptability rates, this program could become a standardized procedure in HD care. The program could be adapted for other populations, e.g., couples facing other genetic neurological disorders.Development and application of statistical models for medical scientific researc

Survival analysis with delayed entry in selected families with application to human longevity

In the field of aging research, family-based sampling study designs are commonly used to study the lifespans of long-lived family members. However, the specific sampling procedure should be carefully taken into account in order to avoid biases. This work is motivated by the Leiden Longevity Study, a family-based cohort of long-lived siblings. Families were invited to participate in the study if at least two siblings were 'long-lived', where 'long-lived' meant being older than 89 years for men or older than 91 years for women. As a result, more than 400 families were included in the study and followed for around 10 years. For estimation of marker-specific survival probabilities and correlations among life times of family members, delayed entry due to outcome-dependent sampling mechanisms has to be taken into account. We consider shared frailty models to model left-truncated correlated survival data. The treatment of left truncation in shared frailty models is still an open issue and the literature on this topic is scarce. We show that the current approaches provide, in general, biased estimates and we propose a new method to tackle this selection problem by applying a correction on the likelihood estimation by means of inverse probability weighting at the family level

Survival analysis with delayed entry in selected families with application to human longevity

In the field of aging research, family-based sampling study designs are commonly used to study the lifespans of long-lived family members. However, the specific sampling procedure should be carefully taken into account in order to avoid biases. This work is motivated by the Leiden Longevity Study, a family-based cohort of long-lived siblings. Families were invited to participate in the study if at least two siblings were 'long-lived', where 'long-lived' meant being older than 89 years for men or older than 91 years for women. As a result, more than 400 families were included in the study and followed for around 10 years. For estimation of marker-specific survival probabilities and correlations among life times of family members, delayed entry due to outcome-dependent sampling mechanisms has to be taken into account. We consider shared frailty models to model left-truncated correlated survival data. The treatment of left truncation in shared frailty models is still an open issue and the literature on this topic is scarce. We show that the current approaches provide, in general, biased estimates and we propose a new method to tackle this selection problem by applying a correction on the likelihood estimation by means of inverse probability weighting at the family level