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Background: Adverse drug reaction reports used in pharmacosurveillance often lack complete information on treatment indication that is important for benefit-risk analyses and clinical and regulatory decision making. A systematic documentation of treatment indication using electronic prescribing applications provides an opportunity to develop new pharmacosurveillance tools that will allow evaluation of drugs by weighing benefits and risks for specific indications, and evaluate off-label prescribing. In addition, interfacing indications with reminders and clinical guidelines can enhance clinical decision making. We investigated the validity of treatment indications documented using an electronic prescribing system at the time of prescribing.Objectives: To determine the sensitivity and positive predictive value (PPV) of an electronic prescribing system in documenting treatment indications at the time of drug prescribing, and to investigate the use of treatment indication data to evaluate off-label prescribing in primary-care practice.Study Design and Setting: We prospectively assessed the validity of documenting treatment indication using an electronic prescribing system by comparing it with treatment indications documented by physician-facilitated medical chart review ('gold standard'). Sensitivity and PPV were evaluated in 338 patients of 22 community-based primary-care physicians in Quebec, Canada, in 2006.Results: The sensitivity of the electronic prescribing system in documenting treatment indication was 98.5% (95% CI 96.5, 99.5) and the PPV of the system in accurately identifying the treatment indication was 97.0% (95% CI 94.2, 98.6). The treatment indication data collected using this system allowed assessment of off-label prescribing.Conclusions: The electronic prescribing system offers a valid method for documenting treatment indication at the time of prescribing. Our results provide strong evidence to support incorporating mandatory recording of treatment indication in integrated electronic prescribing systems to provide a critical piece of information for the evaluation of safety and effectiveness of drugs. [ABSTRACT FROM AUTHOR]

Background. Several surveys have presented the quality of reports on randomized clinical trials (RCTs) published in general and specialty medical journals. The aim of these surveys was to raise scientific consciousness on methodological aspects pertaining to internal and external validity. These reviews have suggested that the methodological quality could be improved. Objective. We conducted a survey of reports on RCTs published in nursing journals to assess their methodological quality. The features we considered inclUded sample size, flow of participants, assessment of baseline comparability, randomization, blinding, and statistical analysis. Methods. We collected data from all reports of RCTs published between January 1994 and December 1997 in Applied Nursing Research, Heart &. Lung and Nursing Research. We hand-searched the journals and included all 54 articles in which authors reported that individuals have been randomly allocated to distinct groups. We collected data using a condensed form of the Consolidated Standards of Reporting Trials (CONSORT) statement for structured reporting of RGs [Begg et al.. 1996). Background A randomized clinical trial (RCT) provides the most valid basis for assessing the benefits of health care interventions. Results of a published RCT will be most influential on patient care if the reader can appreciate both the methodological quality of the trial and the quality of the report. The methodological quality of a trial itself depends on the accurate accomplishment of several fundamental steps. The quality of the report depends on whether the published RCT provides readers with adequate information on the design, Results. Sample size calculations were included in only 22% of the reports. Only 48% of the reports provided information about the type of randomization, and a mere 22% described blinding strategies. Comparisons of baseline characteristics using hypothesis tests were abusively produced in more than 76% of the reports. Excessive use and unstructured reports of significance testing were common [59%\. and all reports failed to provide magnitude of treatment differences with confidence intervals. Conclusions. Better methodological quality in reports of RCTs will contribute to increase the standards of nursing research. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To evaluate the efficacy of a task-oriented walking intervention in improving balance self-efficacy in persons with stroke and to determine whether effects were task-specific, influenced by baseline level of self-efficacy and associated with changes in walking and balance capacity. DESIGN: Secondary analysis of a two-center, observer-blinded, randomized, controlled trial. SETTING: General community. PARTICIPANTS: Ninety-one individuals with a residual walking deficit within 1 year of a first or recurrent stroke. INTERVENTION: Task-oriented interventions targeting walking or upper extremity (UE) function were provided three times a week for 6 weeks. MEASUREMENTS: Activities-specific Balance Confidence Scale, Six-Minute Walk Test, 5-m walk, Berg Balance Scale, and Timed 'Up and Go' administered at baseline and postintervention. RESULTS: The walking intervention was associated with a significantly greater average proportional change in balance self-efficacy than the UE intervention. Treatment effects were largest in persons with low self-efficacy at baseline and for activities relating to tasks practiced. In the walking group, change in balance self-efficacy correlated with change in functional walking capacity (correlation coefficient=0.45, 95% confidence interval=0.16-0.68). Results of multivariable modeling suggested effect modification by the baseline level of depressive symptoms and a prognostic influence of age, sex, comorbidity, time poststroke, and functional mobility on change in self-efficacy. CONCLUSION: Task-oriented walking retraining enhances balance self-efficacy in community-dwelling individuals with chronic stroke. Benefits may be partially the result of improvement in walking capacity. The influence of baseline level of self-efficacy, depressive symptoms, and prognostic variables on treatment effects are of clinical importance and must be verified in future studies. [ABSTRACT FROM AUTHOR]

BACKGROUND: Practice guidelines for breast cancer emphasize the importance of establishing an accurate diagnosis using a minimum number of procedures and selecting optimal treatment regimens. Understanding the determinants of waiting time is essential to develop optimum interventions to reduce delay. OBJECTIVES: The purpose of this study is to estimate the extent to which variability in 1) the number of procedures before surgery and 2) waiting time from initial procedure to surgery are explainable by factors related to the woman, to the provider, and to the care setting. RESEARCH DESIGN: Records of physicians' fee-for-service claims were obtained for 23,370 women undergoing breast cancer surgery in Quebec between 1992 and 1997. Multilevel logistic regression was used to determine predictors of having multiple procedures before surgery. Hierarchical linear regression models were used to identify predictors of waiting time, separately for women with lymph node involvement and without this involvement. RESULTS: Overall, 23% of the women had 3 or more procedures before surgery with significant variation found across hospitals and surgeons. Number of procedures was a strong predictor of waiting time. Waiting time also varied by stage, age, comorbidity, a history of benign disease, surgical setting, calendar time, month of initial procedure, and hospital teaching status. CONCLUSION: Although variability in waiting time was more strongly influenced by the characteristics of the women rather than by physician- or hospital-related factors, most variation remained unexplained by the factors included in this study. To reduce overall waiting time, strategies would need to be systemically applied. [ABSTRACT FROM AUTHOR]

BACKGROUND: As the definitional formula for population attributable fraction is not usually directly usable in applications, separate estimation formulas are required. However, most epidemiology textbooks limit their coverage to Levin's formula, based on the (dichotomous) distribution of the exposure of interest in the population. Few present or explain Miettinen's formula, based on the distribution of the exposure in the cases; and even fewer present the corresponding formulas for situations with more than two levels of exposure. Thus, many health researchers and public health practitioners are unaware of, or are not confident in their use of, these formulas, particularly when they involve several exposure levels, or confounding factors. METHODS/RESULTS: A heuristic approach, coupled with pictorial representations, is offered to help understand and interconnect the structures behind the Levin and Miettinen formulas. The pictorial representation shows how to deal correctly with several exposure levels, and why a commonly used approach is incorrect. Correct and incorrect approaches are also presented for situations where estimates must be aggregated over strata of a confounding factor. [ABSTRACT FROM AUTHOR]

Background: The National Trauma Data Bank (NTDB) is plagued by the problem of missing physiological data. The Glasgow Coma Scale score, Respiratory Rate and Systolic Blood Pressure are an essential part of risk adjustment strategies for trauma system evaluation and clinical research. Missing data on these variables may compromise the feasibility and the validity of trauma group comparisons. Aims: To evaluate the validity of Multiple Imputation (MI) for completing missing physiological data in the National Trauma Data Bank (NTDB), by assessing the impact of MI on 1) frequency distributions, 2) associations with mortality, and 3) risk adjustment. Methods: Analyses were based on 170,956 NTDB observations with complete physiological data (observed data set). Missing physiological data were artificially imposed on this data set and then imputed using MI (MI data set). To assess the impact of MI on risk adjustment, 100 pairs of hospitals were randomly selected with replacement and compared using adjusted Odds Ratios (OR) of mortality. OR generated by the observed data set were then compared to those generated by the MI data set. Results: Frequency distributions and associations with mortality were preserved following MI. The median absolute difference between adjusted OR of mortality generated by the observed data set and by the MI data set was 3.6% (inter-quartile range: 2.4%-6.1%). Conclusions: This study suggests that, provided it is implemented with care, MI of missing physiological data in the NTDB leads to valid frequency distributions, preserves associations with mortality, and does not compromise risk adjustment in inter-hospital comparisons of mortality.

Abstract Background Unlike other malignancies, there is no literature supporting the accuracy of medical claims data for identifying surgical treatments among patients with kidney cancer. We sought to validate externally a previously published Medicare-claims-based algorithm for classifying surgical treatments among patients with early-stage kidney cancer. To achieve this aim, we compared procedure assignments based on Medicare claims with the type of surgery specified in SEER registry data and clinical operative reports. Methods Using linked SEER-Medicare data, we calculated the agreement between Medicare claims and SEER data for identification of cancer-directed surgery among 6,515 patients diagnosed with early-stage kidney cancer. Next, for a subset of 120 cases, we determined the agreement between the claims algorithm and the medical record. Finally, using the medical record as the reference-standard, we calculated the sensitivity, specificity, and positive and negative predictive values of the claims algorithm. Results Among 6,515 cases, Medicare claims and SEER data identified 5,483 (84.1%) and 5,774 (88.6%) patients, respectively, who underwent cancer-directed surgery (observed agreement = 93%, κ = 0.69, 95% CI 0.66 – 0.71). The two data sources demonstrated 97% agreement for classification of partial versus radical nephrectomy (κ = 0.83, 95% CI 0.81 – 0.86). We observed 97% agreement between the claims algorithm and clinical operative reports; the positive predictive value of the claims algorithm exceeded 90% for identification of both partial nephrectomy and laparoscopic surgery. Conclusion Medicare claims represent an accurate data source for ascertainment of population-based patterns of surgical care among patients with early-stage kidney cancer.

Abstract Background Among youth, participation in extracurricular physical activities at school and organised physical activities in the community is associated with higher physical activity levels. The objective was to determine if participation in organised physical activities during early adolescence protects against declines in physical activity levels during adolescence. Methods Every 3 months for 5 years, students initially in grade 7 (aged 12–13 years) completed a 7-day physical activity recall and provided data on the number and type of (extracurricular) physical activities organised at school and in the community in which they took part. To study rates of decline in physical activity, only adolescents who reported an average of ≥5 moderate-vigorous physical activity sessions per week in grade 7 (n = 1028) were retained for analyses. They were categorised as to whether or not they were involved in organised physical activities in grade 7. We used generalized estimating equation Poisson regression to compare the rate of decline in number of moderate-vigorous physical activity sessions per week during adolescence between initially physically active students who participated in organised physical activity in grade 7 and those who did not. Results In grade 7, about 87% of physically active adolescents reported taking part in at least one organised physical activity. Compared to active adolescents not involved in organised physical activities, baseline involvement in physical activity was 42% (95% CI 26–59%) higher among those involved in organised physical activity (mean number of moderate-vigorous physical activity sessions per week = 14.6 ± 13.1 vs 10.4 ± 9.0). Physical activity declined by 8% per year in both groups. Results were similar in analyses that examined the effect of school or community-based physical activities separately. Conclusion Although participation in organised physical activities during early adolescence is associated with more physical activity throughout secondary school, participation in such activities does not protect against declines in physical activity over time.

Abstract Background The association between stress and morale among general practitioners (GP) is well documented. However, the impact of GP stress or low morale on patient care is less clear. GPs in the UK now routinely survey patients about the quality of their care including organizational issues and consultation skills and the General Practice Assessment Questionnaire (GPAQ) is widely used for this purpose. We aimed to see if there was a relationship between doctor morale as measured by a validated instrument, the Morale Assessment in General Practice Index (MAGPI) and scores in the GPAQ. Methods All GPs in Lothian, Scotland who were collecting GPAQ data were approached and asked to complete the MAGPI. Using an anonymised linkage system, individual scores on the MAGPI were linked to the doctors' GPAQ scores. Levels of association between the scores were determined by calculating rank correlations at the level of the individual doctor. Hypothesised associations between individual MAGPI and GPAQ items were also assessed. Results 276 of 475 GPs who were approached agreed to complete a MAGPI questionnaire and successfully collected anonymous GPAQ data from an average of 49.6 patients. There was no significant correlation between the total MAGPI score and the GPAQ communication or enablement scale. There were weak correlations between "control of work" in the MAGPI scale and GPAQ items on waiting times to see doctors (r = 0.24 p < 0.01). Doctors who perceived that their patients viewed them negatively also scored lower on individual communication, accessibility and continuity of care GPAQ items. Conclusion This study showed no relationship between overall GP morale and patient perception of performance. There was a weak relationship between patients' perceptions ofquality and doctors' beliefs about their workload and whether patients value them. Further research is required to elucidate the complex relationship between workload, morale and patients' perception of care.

BACKGROUND: Indirect evidence suggests that prolonged treatment with warfarin might be associated with a decreased incidence of urogenital cancer. We aimed to assess this association in a large population-based study. METHODS: Beneficiaries of Saskatchewan Health who were eligible for prescription drug benefits and aged 50 years or over with no history of cancer since 1967 were enrolled into a nested, matched case-control study. 19 412 new cases of urogenital cancer diagnosed between Jan 1, 1981, and Dec 31, 2002, were identified by use of information from the Saskatchewan Cancer Agency registry. For each case, six controls, totalling 116 470, who were matched for age, sex, and time of diagnosis were selected randomly. Conditional logistic regression analysis was used to calculate adjusted incidence rates of urogenital cancer in relation to warfarin use. FINDINGS: Compared with men who never used warfarin, men with 4 years of warfarin use had an adjusted incidence rate of 0.80 (95% CI [0.65-0.99]). For warfarin use 76-100% of the time, the adjusted rate ratios were 0.80 (0.66-0.96) during year 2 preceding diagnosis of prostate cancer, 0.76 (0.62-0.94) during year 3, and 0.67 (0.53-0.86) during year 4. No significant association was found between warfarin and risk of other urogenital cancers. INTERPRETATION: Our results suggest that warfarin has an antitumour effect that is specific to prostate cancer. Further investigation, with more complete assessment of confounders and that addresses the effect of warfarin on mortality of prostate cancer, is warranted. [ABSTRACT FROM AUTHOR]

Background: In oncology trials, response evaluation criteria are pivotal in developing new treatments. This study examines the influence of measurement variability in brain lesions on response classification, considering long-standing cut-offs for progression and response were determined before the era of submillimeter resolutions of medical imaging., Methods: We replicate a key study using modern radiological tools. Sixteen radiologists were tasked with measuring twelve near-spherical brain tumors using visual estimation (eyeballing), diameter measurements and artificial intelligence (AI) assisted segmentations. Analyses for inter- and intraobserver variability from the original were replicated. Additionally, we researched the effect of measurement error on the misclassification of progressive disease using a computer simulation model., Results: The combined effect of intra- and interobserver error varied between 13.6 and 22.2% for eyeballing and 6.8-7.2% for diameter measurement, using AI-assisted segmentation as reference. We observed erroneously declared progression (cut-off at 20% increase) in repeat measurements of the same tumor in 25.5% of instances for eyeballing and in 1.1% for diameter measurements. Response (cut-off at 30% decrease) was erroneously declared in 12.3% for eyeballing and in 0% for diameter measurements. The simulation model demonstrated a more pronounced impact of measurement error on cases with fewer total number of lesions., Conclusions: This study provides a minimum expected measurement error using real-world data. The impact of measurement error on response evaluation criteria misclassification in brain lesions was most pronounced for eyeballing. Future research should focus on measurement error for different tumor types and assess its impact on response classification during patient follow-up., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Introduction: Screening trials and meta-analyses emphasize the ratio of cancer death rates in screening and control arms. However, this measure is diluted by the inclusion of deaths from cancers that only became detectable after the end of active screening., Methods: We review traditional analysis of cancer screening trials and show that ratio estimates are inevitably biased to the null, because follow-up (FU) must continue beyond the end of the screening period and thus includes cases only becoming detectable after screening ends. But because such cases are expected to occur in equal numbers in the two arms, calculation of the difference between the number of cancer deaths in the screening and control arms avoids this dilutional bias. This difference can be set against the number of invitations to screening; we illustrate by reanalyzing data from all trials of tomography screening of lung cancer (LC) using this measure., Results: In nine trials of LC screening from 2000 to 2013, a total of 94,441 high-risk patients were invited to be in screening or control groups, with high participation rates (average 95%). In the older trials comparing computed tomography to chest X-ray, 88,285 invitations averted 83 deaths (1068 per death averted (DA)). In the six more recent trials with no screening in the control group, 69,976 invitations averted 121 deaths (577 invitations per DA)., Discussion: Screens per DA is an undiluted measure of screening's effect and it is unperturbed by the arbitrary duration of FU. This estimate can be useful for program planning and informed consent., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Purpose: We questioned whether an intensive experiential core course would change medical students' intention to practice mindful clinical congruence. Our primary hypothesis was that we would see more of a change in the intention to practice mindful clinical congruence in those who had taken versus not yet taken our course., Methods: From a class of 179 in second year we recruited 57 (32%) students who had been already divided into three groups that completed the course in successive periods. We measured mindful clinical congruence using a questionnaire developed and evaluated for validity. We also measured students' level of stress to determine if any effects we saw were related to stress reduction., Results: Students who had just completed the course showed a greater intention to practice mindful clinical congruence than students who had not yet started the course. There was an apparent slight increase in perceived stress in those who had completed our course., Conclusions: We can change students' intention to practice mindfully and congruently, which we believe will prevent a decline in compassion and ethical values in clerkship. The results did not appear to be explained by a decrease in stress in students who completed the course., Competing Interests: The authors report that there are no competing interests to declare., (© 2024 Hutchinson, Hanley, Liben, Lubarsky; licensee Synergies Partners.)

Evaluating the prognostic performance of candidate markers for future disease onset or progression is one of the major goals in medical research. A marker's prognostic performance refers to how well it separates patients at the high or low risk of a future disease state. Often the discriminative performance of a marker is affected by the patient characteristics (covariates). Time-dependent receiver operating characteristic (ROC) curves that ignore the informativeness of the covariates will lead to biased estimates of the accuracy parameters. We propose a time-dependent ROC curve that accounts for the informativeness of the covariates in the case of censored data. We propose inverse probability weighted (IPW) estimators for estimating the proposed accuracy parameters. We investigate the performance of the IPW estimators through simulation studies and real-life data analysis., (© 2023 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

Life expectancy figures for countries and population segments are increasingly being reported to more decimal places and used as indicators of the strengths or failings of countries' health and social systems. Reports seldom quantify their intrinsic statistical imprecision or the age-specific numbers of deaths that determine them. The SE formulas available to compute imprecision are all model based. This note adds a more intuitive data-based SE method and extends the jackknife to the analysis of event rates more generally. It also describes the relationships between the magnitude of the SE and the numbers of person-years and deaths on which it is based. These relationships can help quantify the statistical noise present in published year-to-year differences in life expectancies, as well as in same-year differences between or within countries. Agencies and investigators are encouraged to use one of these SEs to report the imprecision of life expectancy numbers and to tailor the number of decimal places accordingly. ( Am J Public Health . 2022;112(8):1151-1160. https://doi.org/10.2105/AJPH.2022.306805).

Epidemiologists commonly use an adjusted hazard ratio or incidence density ratio, or a standardized mortality ratio, to measure a difference in all-cause mortality rates. They seldom translate it into an age-, time-, or probability-based measure that would be easier to communicate and to relate to. Several articles have shown how to translate from a standardized mortality ratio or hazard ratio to a longevity difference, a difference in actuarial ages, or a probability of being outlived. In this paper, we describe the settings where these translations are and are not appropriate and provide some of the heuristics behind the formulae. The tools that yield differences in "effective age" and in longevity are applicable when both 1) the mortality rate ratio (hazard ratio) is constant over age and 2) the rates themselves are log-linear in age. The "probability/odds of being outlived" metric is applicable whenever the first condition holds, and thus it provides no direct information on the magnitude of the effective age/longevity difference., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Competing Interests: None of the three authors disclosed any relationship/activity/interest that is related to the content of this manuscript.

Background: Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be used for smoothing by considering the knot coefficients from a regression spline as random effects. The resulting models are called semiparametric mixed models (SPMMs). Allowing the random knot coefficients to follow a normal distribution with mean zero and a constant variance is equivalent to using a penalized spline with a ridge regression type penalty. We introduce the least absolute shrinkage and selection operator (LASSO) type penalty in the SPMM setting by considering the coefficients at the knots to follow a Laplace double exponential distribution with mean zero., Methods: We adopt a Bayesian approach and use the Markov Chain Monte Carlo (MCMC) algorithm for model fitting. Through simulations, we compare the performance of curve fitting in a SPMM using a LASSO type penalty to that of using ridge penalty for binary data. We apply the proposed method to obtain smooth curves from data on the relationship between the amount of pack years of smoking and the risk of developing chronic obstructive pulmonary disease (COPD)., Results: The LASSO penalty performs as well as ridge penalty for simple shapes of association and outperforms the ridge penalty when the shape of association is complex or linear., Conclusion: We demonstrated that LASSO penalty captured complex dose-response association better than the Ridge penalty in a SPMM.

Small-sample confidence intervals for the mean of a Poisson distribution have been used since the 1930s. They can be computed by trial and error, or using a computation-saving link that few are aware of and that, even if they are, is neither intuitive nor easy to remember. I trace how and why this link has been used, even if the basis for it has been lost or ignored. I promote a direct and more meaningful link that can be easily used today without having to resort to tables or approximations suited to hand calculators. More importantly, this (time-based) link is instructive and intuitive, and thus more easily derived and understood., (© 2019 John Wiley & Sons, Ltd.)

Background: The analysis of twin data presents a unique challenge. Second-born twins on average weigh less than first-born twins and have an elevated risk of perinatal mortality. It is not clear whether the risk difference depends on birth order or their relative birth weight. This study evaluates the association between birth order and perinatal mortality by birth order-specific weight difference in twin pregnancies., Methods: We adopt generalized additive mixed models (GAMMs) which are a flexible version of generalized linear mixed models (GLMMs), to model the association. Estimation of such models for correlated binary data is challenging. We compare both Bayesian and likelihood-based approaches for estimating GAMMs via simulation. We apply the methods to the US matched multiple birth data to evaluate the association between twins' birth order and perinatal mortality., Results: Perinatal mortality depends on both birth order and relative birthweight. Simulation results suggest that the Bayesian method with half-Cauchy priors for variance components performs well in estimating all components of the GAMM. The Bayesian results were sensitive to prior specifications., Conclusion: We adopted a flexible statistical model, GAMM, to precisely estimate the perinatal mortality risk differences between first- and second-born twins whereby birthweight and gestational age are nonparametrically modelled to explicitly adjust for their effects. The risk of perinatal mortality in twins was found to depend on both birth order and relative birthweight. We demonstrated that the Bayesian method estimated the GAMM model components more reliably than the frequentist approaches.

Background: High discontinuation rates remain a challenge for home hemodialysis (HHD) and peritoneal dialysis (PD). We compared technique failure risks among Canadian patients receiving HHD and PD., Methods: Using the Canadian Organ Replacement Register, we studied adult patients who initiated HHD or PD within 1 year of beginning dialysis between 2000 and 2012, with follow-up until 31 December 2013. Technique failure was defined as a transfer to any alternative modality for a period of ≥60 days. Technique survival between HHD and PD was compared using a Fine and Gray competing risk model. We also examined the time dependence of technique survival, the association of patient characteristics with technique failure and causes of technique failure., Results: Between 2000 and 2012, 15 314 patients were treated with a home dialysis modality within 1 year of dialysis initiation: 14 461 on PD and 853 on HHD. Crude technique failure rates were highest during the first year of therapy for both home modalities. During the entire period of follow-up, technique failure was lower with HHD compared with PD (adjusted hazard ratio = 0.79; 95% confidence interval 0.69-0.90). However, the relative technique failure risk was not proportional over time and the beneficial association with HHD was only apparent after the first year of dialysis. Comparisons also varied among subgroups and the superior technique survival associated with HHD relative to PD was less pronounced in more recent years and among older patients. Predictors of technique failure also differed between modalities. While obesity, smoking and small facility size were associated with higher technique failure in both PD and HHD, the association with age and gender differed. Furthermore, the majority of discontinuation occurred for medical reasons in PD (38%), while the majority of HHD patients experienced technique failure due to social reasons or inadequate resources (50%)., Conclusions: In this Canadian study of home dialysis patients, HHD was associated with better technique survival compared with PD. However, patterns of technique failure differed significantly among these modalities. Strategies to improve patient retention across all home dialysis modalities are needed., (© The Author(s) 2019. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)

With greater access to regression-based methods for confounder control, the etiologic study with individual matching, analyzed by classical (calculator) methods, lost favor in recent decades. This design was costly, and the data sometimes mis-analyzed. Now, with Big Data, individual matching becomes an economical option. To many, however, conditional logistic regression, commonly used to estimate the incidence density ratio parameter, is somewhat of a black box whose output is not easily checked. An epidemiologist-statistician pair recently proposed a new estimator that is easily applied to data from individually-matched series with a 2:1 ratio (and no other confounding variables) using just a hand calculator or spreadsheet. Surprisingly-or possibly not-they overlooked classical estimators developed in earlier decades. This prompts me to re-introduce some of these, to highlight their considerable flexibility and ease of use, and to update them. Nowadays, for any matching ratio (M:1), the Maximum Likelihood result can be easily computed from data gathered under the matched design in two different ways, each using just the summary data. One is via any binomial regression program that allows offsets, applied to just M 'rows' of data. The other is by hand! The aim of this note is not to save on computation; instead, it is to make connections between classical and regression-based methods, to promote terminology that reflects the concepts and structure of the etiologic study, and to focus attention on what parameter is being estimated.

Objectives: The primary objective of this study was to identify the predictors of new-onset psychological distress available in routinely collected administrative health databases for women diagnosed with breast cancer. The secondary objective was to explore whether the predictors vary based on the period of cancer care. Methods: A population-based cohort study followed 16,495 female patients with newly diagnosed breast cancer who did not experience psychological distress during the 14 months before breast cancer surgery. The incidence of psychological distress was reported overall and by type of mental health problem. Time-varying Cox proportional hazards models were developed to identify predictors of new-onset psychological distress during 2 key periods of cancer care: (1) hospital-based treatment during which women undergo treatment with breast surgery, chemotherapy, and/or radiation, and (2) 1-year transitional survivorship when women begin follow-up care. Results: The incidence of psychological distress was 16% within each period. Anxiety was present in 85.1% and 65.5% of new cases during hospital-based treatment and transitional survivorship, respectively. Predictors during both periods were younger age, receipt of axillary lymph node dissection, rheumatologic disease, and baseline menopausal symptoms, as well as new opioid dispensations, emergency department visits, and hospital contacts that occurred during follow-up. Other predictors varied based on the period of cancer care. More advanced breast cancer and type of treatment were associated with onset of psychological distress during hospital-based treatment. Psychological distress during transitional survivorship was predicted by diagnosis of localized breast disease, shorter duration of hospital-based treatment, receipt of additional hospital-based treatment in survivorship, and newly diagnosed comorbidities or symptoms. Conclusions: This study identified the predictors of new-onset psychological distress available in routinely collected administrative health databases, and showed how predictors change between hospital-based treatment and transitional survivorship periods. The results highlight the importance of developing predictive models tailored to the period of cancer care., (Copyright © 2018 by the National Comprehensive Cancer Network.)

My early years as a statistician were with the Eastern Co-operative Oncology Group and the Radiation Oncology Therapy Group; three of these years were spent at the Sidney Farber Cancer Institute. Later, I collaborated widely with investigators in many clinical research areas. I reflect on the "statistical interrogations of nature" I saw (and helped some of these) investigators plan and carry out. I look back on their (and my own) statistical behaviors when interpreting the information these interrogations produced and-using a few vignettes and some computer-generated observations-draw some lessons from them. These mainly have to do with making too much of one's data.

The mortality impact in cancer screening trials and population programs is usually expressed as a single hazard ratio or percentage reduction. This measure ignores the number/spacing of rounds of screening, and the location in follow-up time of the averted deaths vis-a-vis the first and last screens. If screening works as intended, hazard ratios are a strong function of the two Lexis time-dimensions. We show how the number and timing of the rounds of screening can be included in a model that specifies what each round of screening accomplishes. We show how this model can be used to disaggregate the observed reductions (i.e., make them time-and screening-history specific), and to project the impact of other regimens. We use data on breast cancer screening to illustrate this model, which we had already described in technical terms in a statistical journal. Using the numbers of invitations different cohorts received, we fitted the model to the age- and follow-up-year-specific numbers of breast cancer deaths in Funen, Denmark. From November 1993 onwards, women aged 50-69 in Funen were invited to mammography screening every two years, while those in comparison regions were not. Under the proportional hazards model, the overall fitted hazard ratio was 0.82 (average reduction 18%). Using a (non-proportional-hazards) model that included the timing information, the fitted reductions ranged from 0 to 30%, being largest in those Lexis cells that had received the greatest number of invitations and where sufficient time had elapsed for the impacts to manifest. The reductions produced by cancer screening have been underestimated by inattention to their timing. By including the determinants of the hazard ratios in a regression-type model, the proposed approach provides a way to disaggregate the mortality reductions and project the reductions produced by other regimes/durations.

Our objective was to compare breast cancer mortality in two regions of the Republic of Ireland that introduced a screening programme eight years apart, and to estimate the steady-state mortality deficits the programme will produce. We carried out age- and year-matched between-region comparison of breast cancer mortality rates, and of incidence rates of stage 2-4 breast cancer, in the eligible cohorts. The regions comprised counties that, beginning in early 2000 (region 1) and late 2007 (region 2), invited women aged 50-64 to biennial mammography screening. The data were supplied by the National Cancer Registry, Central Statistics Office. As impact measures, we used age-and-year-matched mortality (from breast cancers diagnosed from 2000 onwards), rate ratios and incidence rate ratios in the compared regions from 2000 to 2013. Ratios were adjusted for between-region differences in background rates. In cohorts too old to be invited, death rates in regions 1 and 2 were 702 per 0.91 and 727 per 0.90 million women-years respectively (Ratio 0.96). In the eligible cohorts, they were 1027 per 2.9 and 1095 per 2.67 (Ratio 0.88). Thus, rates in cohorts that could have benefitted were 9% lower in region 1 than region 2: (95%CI: -20%, +4%). The incidence rates of stage 2-4 breast cancer were 7% lower in region 2 than region 1 over the entire 14 year period, and 20% lower in 2007, i.e., before the screening in region 2 began to narrow the difference. Since mortality reductions due to screening only manifest after several years, the full impact of screening has not yet been realized in region 1. The lower rate observed in that region is a conservative estimate of the steady state benefit. Additional deaths would have been averted had screening continued beyond age 64.

Panel study designs are common in environmental epidemiology, whereby repeated measurements are collected from a panel of subjects to evaluate short-term within-subject changes in response variables over time. In planning such studies, questions of how many subjects to include and how many different exposure conditions to measure are commonly asked at the design stage. In practice, these choices are constrained by budget, logistics, and participant burden and must be carefully balanced against statistical considerations of precision and power. In this article, we provide intuitive sample size formulae for the precision of regression coefficients derived from panel studies and show how they can be applied in planning such studies. We show that there are five determinants of the precision with which regression coefficients can be estimated: (1) the residual variance of the responses; (2) the variance of the slopes; (3) the number of subjects; (4) the number of measurements/subject; and (5) the within-subject range of the exposure values "X" at which the responses are measured. The planning of such studies would be greatly improved if investigators regularly reported all of the variance components in fitted random-effects models: currently, literature values for the relevant variance parameters are often not readily available and must be estimated through pilot studies or subjective estimates of "reasonable values."

Purpose: Unmanaged distress has been shown to adversely affect survival and quality of life in breast cancer survivors. Fortunately, distress can be managed and even prevented with appropriate evidence-based interventions. Therefore, the objective of this systematic review was to synthesize the published literature around predictors of distress in female breast cancer survivors to help guide targeted intervention to prevent distress., Methods: Relevant studies were located by searching MEDLINE, Embase, PsycINFO, and CINAHL databases. Significance and directionality of associations for commonly assessed candidate predictors (n ≥ 5) and predictors shown to be significant (p ≤ 0.05) by at least two studies were summarized descriptively. Predictors were evaluated based on the proportion of studies that showed a significant and positive association with the presence of distress., Results: Forty-two studies met the target criteria and were included in the review. Breast cancer and treatment-related predictors were more advanced cancer at diagnosis, treatment with chemotherapy, longer primary treatment duration, more recent transition into survivorship, and breast cancer recurrence. Manageable treatment-related symptoms associated with distress included menopausal/vasomotor symptoms, pain, fatigue, and sleep disturbance. Sociodemographic characteristics that increased the risk of distress were younger age, non-Caucasian ethnicity, being unmarried, and lower socioeconomic status. Comorbidities, history of mental health problems, and perceived functioning limitations were also associated. Modifiable predictors of distress were lower physical activity, lower social support, and cigarette smoking., Conclusions: This review established a set of evidence-based predictors that can be used to help identify women at higher risk of experiencing distress following completion of primary breast cancer treatment.

In previous articles in the American Journal of Epidemiology (Am J Epidemiol. 2013;177(5):431-442) and American Journal of Public Health (Am J Public Health. 2013;103(10):1895-1901), Masters et al. reported age-specific hazard ratios for the contrasts in mortality rates between obesity categories. They corrected the observed hazard ratios for selection bias caused by what they postulated was the nonrepresentativeness of the participants in the National Health Interview Study that increased with age, obesity, and ill health. However, it is possible that their regression approach to remove the alleged bias has not produced, and in general cannot produce, sensible hazard ratio estimates. First, we must consider how many nonparticipants there might have been in each category of obesity and of age at entry and how much higher the mortality rates would have to be in nonparticipants than in participants in these same categories. What plausible set of numerical values would convert the ("biased") decreasing-with-age hazard ratios seen in the data into the ("unbiased") increasing-with-age ratios that they computed? Can these values be encapsulated in (and can sensible values be recovered from) one additional internal variable in a regression model? Second, one must examine the age pattern of the hazard ratios that have been adjusted for selection. Without the correction, the hazard ratios are attenuated with increasing age. With it, the hazard ratios at older ages are considerably higher, but those at younger ages are well below one. Third, one must test whether the regression approach suggested by Masters et al. would correct the nonrepresentativeness that increased with age and ill health that I introduced into real and hypothetical data sets. I found that the approach did not recover the hazard ratio patterns present in the unselected data sets: the corrections overshot the target at older ages and undershot it at lower ages.

Objective: The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression., Study Design and Setting: This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates., Results and Conclusion: By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres., (Copyright © 2016 Elsevier Inc. All rights reserved.)