Estimating excess hazard ratios and net survival when covariate data are missing: strategies for multiple imputation.

BACKGROUND: Net survival is the survival probability we would observe if the disease under study were the only cause of death. When estimated from routinely collected population-based cancer registry data, this indicator is a key metric for cancer control. Unfortunately, such data typically contain a non-negligible proportion of missing values on important prognostic factors (eg, tumor stage). METHODS: We carried out an empirical study to compare the performance of complete records analysis and several multiple imputation strategies when net survival is estimated via a flexible parametric proportional hazards model that includes stage, a partially observed categorical covariate. Starting from fully observed cancer registry data, we induced missingness on stage under three scenarios. For each of these scenarios, we simulated 100 incomplete datasets and evaluated the performance of the different strategies. RESULTS: Ordinal logistic models are not suitable for the imputation of tumor stage. Complete records analysis may lead to grossly misleading estimates of net survival, even when the missing data mechanism is conditionally independent of survival time given the covariates and the bias on the excess hazard ratios estimates is negligible. CONCLUSIONS: As key covariates are unlikely missing completely at random, studies estimating net survival should not use complete records. When the missingness can be inferred from available data, appropriate multiple imputation should be performed. In the context of flexible parametric proportional hazards models with a partially observed stage covariate, a multinomial logistic imputation model for stage should be used and should include the Nelson-Aalen cumulative hazard estimate and the event indicator

Correcting bias due to missing stage data in the non-parametric estimation of stage-specific net survival for colorectal cancer using multiple imputation.

BACKGROUND: Population-based net survival by tumour stage at diagnosis is a key measure in cancer surveillance. Unfortunately, data on tumour stage are often missing for a non-negligible proportion of patients and the mechanism giving rise to the missingness is usually anything but completely at random. In this setting, restricting analysis to the subset of complete records gives typically biased results. Multiple imputation is a promising practical approach to the issues raised by the missing data, but its use in conjunction with the Pohar-Perme method for estimating net survival has not been formally evaluated. METHODS: We performed a resampling study using colorectal cancer population-based registry data to evaluate the ability of multiple imputation, used along with the Pohar-Perme method, to deliver unbiased estimates of stage-specific net survival and recover missing stage information. We created 1000 independent data sets, each containing 5000 patients. Stage data were then made missing at random under two scenarios (30% and 50% missingness). RESULTS: Complete records analysis showed substantial bias and poor confidence interval coverage. Across both scenarios our multiple imputation strategy virtually eliminated the bias and greatly improved confidence interval coverage. CONCLUSIONS: In the presence of missing stage data complete records analysis often gives severely biased results. We showed that combining multiple imputation with the Pohar-Perme estimator provides a valid practical approach for the estimation of stage-specific colorectal cancer net survival. As usual, when the percentage of missing data is high the results should be interpreted cautiously and sensitivity analyses are recommended

audit_cc: a Stata command for the analysis of matched case-control audits of cervical cancer screening

BACKGROUND AND OBJECTIVES: Cervical screening programmes are crucial for the early diagnosis and prevention of cancer of the cervix. Regular auditing is vital for ensuring that these programmes achieve their full potential and meet their objectives in practice. Unfortunately, the time and skills required for the statistical analysis of the data collected are often important limiting factors. Comparisons across countries and over time have also been particularly difficult due to a lack of standardized definitions and methodology. We aimed to overcome these problems. METHODS: Using the statistical software Stata, we developed a new command called audit_cc for the analysis of matched case-control audits of cervical cancer screening. Analyses are reported for two measures of screening history: time since last test and time since last negative test. RESULTS: The command carries out the data manipulation which is required for the analysis and allows to save the resulting data set in an external file for further investigations. It promotes consistent evaluations of screening programmes over time and across studies and facilitates the creation of automatic publication-quality reports, which are especially useful in the context of routine audits. CONCLUSIONS: audit_cc is a valid tool that not only simplifies the analysis and reporting of cervical screening audits but also allows meaningful international comparisons. Although it is specific for cervical cancer, it can be seen as an example of how the standardisation of exposure definitions and key methodological issues can enable consistent and comparable evaluations of screening programmes across different countries and settings

Applications of -gllamm- in health evaluation studies

-gllamm- provides a framework within which many of the more difficult analyses required for trials and intervention studies may be undertaken. Treatment effect estimation in the presence of non-compliance can be undertaken using instrumental variable (IV) methods. We illustrate how -gllamm- can be used for IV estimation for the full range of types of treatment and outcome measures and describe how missing data may be tackled on an assumption of latent ignorability. Alternative approaches to account for clustering and analyse cluster-randomised studies will also be described. Quality of life and economic evaluation of outcomes often makes use of discrete choice and stated preference experiments in which illness scenarios are assessed. We illustrate how -gllamm- can be used for the analysis of data from such studies, whether these are in the common form of paired comparisons or the more complex case where multiple scenarios are ranked. Examples from studies of a school-based smoking intervention, a re-employment encouragement experiment, a group therapy trial and of quality-of-life with rheumatoid arthritis will be considered.

Nanoimprinted, Submicrometric, MOF-Based 2D Photonic Structures: Toward Easy Selective Vapors Sensing by a Smartphone Camera

International audience2D photonic metal–oxide-framework-based homo- and hetero-structures are fabricated by soft lithographic approaches. As shown by A. Cattoni, M. Faustini and co-workers, these materials can be used as selective photonic sensing platforms. Detection of toxic vapors such as styrene are performed using an easy transduction method, compatible with smart-phone camera technologies

Statin prescribing for people with severe mental illnesses: a staggered cohort study of 'real-world' impacts

OBJECTIVES: To estimate the 'real-world effectiveness of statins for primary prevention of cardiovascular disease (CVD) and for lipid modification in people with severe mental illnesses (SMI), including schizophrenia and bipolar disorder. DESIGN: Series of staggered cohorts. We estimated the effect of statin prescribing on CVD outcomes using a multivariable Poisson regression model or linear regression for cholesterol outcomes. SETTING: 587 general practice (GP) surgeries across the UK reporting data to The Health Improvement Network. PARTICIPANTS: All permanently registered GP patients aged 40-84 years between 2002 and 2012 who had a diagnosis of SMI. Exclusion criteria were pre-existing CVD, statin-contraindicating conditions or a statin prescription within the 24 months prior to the study start. EXPOSURE: One or more statin prescriptions during a 24-month 'baseline' period (vs no statin prescription during the same period). MAIN OUTCOME MEASURES: The primary outcome was combined first myocardial infarction and stroke. All-cause mortality and total cholesterol concentration were secondary outcomes. RESULTS: We identified 2944 statin users and 42 886 statin non-users across the staggered cohorts. Statin prescribing was not associated with significant reduction in CVD events (incident rate ratio 0.89; 95% CI 0.68 to 1.15) or all-cause mortality (0.89; 95% CI 0.78 to 1.02). Statin prescribing was, however, associated with statistically significant reductions in total cholesterol of 1.2 mmol/L (95% CI 1.1 to 1.3) for up to 2 years after adjusting for differences in baseline characteristics. On average, total cholesterol decreased from 6.3 to 4.6 in statin users and 5.4 to 5.3 mmol/L in non-users. CONCLUSIONS: We found that statin prescribing to people with SMI in UK primary care was effective for lipid modification but not CVD events. The latter finding may reflect insufficient power to detect a smaller effect size than that observed in randomised controlled trials of statins in people without SMI

Factors associated with discontinuation of antidepressant treatment after a single prescription among patients aged 55 or over:evidence from English primary care

Purpose: Antidepressants are frequently prescribed to older people with depression but little is known on predictors of discontinuation in this population. We therefore investigated factors associated with early discontinuation of antidepressants in older adults with new diagnoses or symptoms of depression in English primary care. / Methods: Data from a nationally representative cohort of patients aged 55 and over were used to evaluate the association between discontinuation of antidepressant medication after a single prescription and potential explanatory variables, including socio-demographic factors, polypharmacy and agerelated problems such as dementia. / Results: Overall, during the study period we observed 34,715 new courses of antidepressant treatment initiated after recorded symptoms or diagnoses of depression. Antidepressant discontinuation after a single prescription was more common in people with depressive symptoms (32%) than in those with diagnosed depression (21.6%). In those diagnosed with depression and in women with depressive symptoms we found that, after adjusting for confounders, the odds of early discontinuation significantly increased after age 65 with a peak at around age 80 and then either levelled or reduced thereafter. Early discontinuation was also significantly less common in people with dementia and in those with diagnosed depression living in more rural areas. / Conclusions: Early discontinuation of antidepressants increases in the post retirement years and is higher in those with no formal diagnosis of depression, those without dementia and those with diagnosed depression living in urban areas. Alternative treatment strategies, such as non-drug therapies, or more active patient follow-up should be further considered in these circumstances

Combining a Genetically Engineered Oxidase with Hydrogen-Bonded Organic Frameworks (HOFs) for Highly Efficient Biocomposites

Enzymes incorporated into hydrogen‐bonded organic frameworks (HOFs) via bottom‐up synthesis are promising biocomposites for applications in catalysis and sensing. Here, we explored synthetic incorporation of d‐amino acid oxidase (DAAO) with the metal‐free tetraamidine/tetracarboxylate‐based BioHOF‐1 in water. N‐terminal enzyme fusion with the positively charged module Z(basic2) strongly boosted the loading (2.5‐fold; ≈500 mg enzyme g(material) (−1)) and the specific activity (6.5‐fold; 23 U mg(−1)). The DAAO@BioHOF‐1 composites showed superior activity with respect to every reported carrier for the same enzyme and excellent stability during catalyst recycling. Further, extension to other enzymes, including cytochrome P450 BM3 (used in the production of high‐value oxyfunctionalized compounds), points to the versatility of genetic engineering as a strategy for the preparation of biohybrid systems with unprecedented properties