Adjusted indices of multiple deprivation to enable comparisons within and between constituent countries of the UK including an illustration using mortality rates

This is the final version of the article. Available from BMJ Publishing Group via the DOI in this record.Objectives Social determinants can have a major impact on health and as a consequence substantial inequalities are seen between and within countries. The study of inequalities between countries relies on having accurate and consistent measures of deprivation across the country borders. However, in the UK most socioeconomic deprivation measures are not comparable between countries. We give a method of adjusting the Indices of Multiple Deprivation (IMD) for use across the UK, describe the deprivation of each UK country, and show the problems introduced by naïvely using country-specific deprivation measures in a UK-wide analysis of mortality rates. Setting/participants 42 148 geographic areas covering the population of the UK. Outcome measures Adjusted IMD scores based on the income and employment domains of country-specific IMD scores, adjusting for the contribution of other domains. The mortality rate among people aged under 75 years standardised to the UK age structure was compared between country-specific and UK-adjusted IMD quintiles. Results Of the constituent countries of the UK, Northern Ireland was the most deprived with 37% of the population living in areas in the most deprived fifth of the UK, followed by Wales with 22% of the population living in the most deprived fifth of the UK. England and Scotland had similar levels of deprivation. Deprivation-specific mortality rates were similar in England and Wales. Northern Ireland had lower mortality rates than England for each deprivation group, with similar differences for each group. Scotland had higher mortality rates than England for each deprivation group, with larger differences for more deprived groups. Conclusions Analyses of between-country and within-country inequalities by socioeconomic position should use consistent measures; failing to use consistent measures may give misleading results. The published adjusted IMD scores we describe allow consistent analysis across the UK

Missing data and chance variation in public reporting of cancer stage at diagnosis: Cross-sectional analysis of population-based data in England

This is the final published version. Available from Elsevier via the DOI in this record.Background: The percentage of cancer patients diagnosed at an early stage is reported publicly for geographically-defined populations corresponding to healthcare commissioning organisations in England, and linked to pay-for-performance targets. Given that stage is incompletely recorded, we investigated the extent to which this indicator reflects underlying organisational differences rather than differences in stage completeness and chance variation. Methods We used population-based data on patients diagnosed with one of ten cancer sites in 2013 (bladder, breast, colorectal, endometrial, lung, ovarian, prostate, renal, NHL, and melanoma). We assessed the degree of bias in CCG (Clinical Commissioning Group) indicators introduced by missing-is-late and complete-case specifications compared with an imputed ‘gold standard’. We estimated the Spearman-Brown (organisation-level) reliability of the complete-case specification. We assessed probable misclassification rates against current pay-for-performance targets. Results Under the missing-is-late approach, bias in estimated CCG percentage of tumours diagnosed at an early stage ranged from −2 to −30 percentage points, while bias under the complete-case approach ranged from −2 to +7 percentage points. Using an annual reporting period, indicators based on the least biased complete-case approach would have poor reliability, misclassifying 27/209 (13%) CCGs against a pay-for-performance target in current use; only half (53%) of CCGs apparently exceeding the target would be correctly classified in terms of their underlying performance. Conclusions Current public reporting schemes for cancer stage at diagnosis in England should use a complete-case specification (i.e. the number of staged cases forming the denominator) and be based on three-year reporting periods. Early stage indicators for the studied geographies should not be used in pay-for-performance schemes.Cancer Research U

The influence of patient case mix on public health area statistics for cancer stage at diagnosis: a cross-sectional study

This is the final version. Available on open access from OUP via the DOI in this recordBACKGROUND: statistics comparing the stage at diagnosis of geographically defined populations of cancer patients are increasingly used in public reporting to monitor geographical inequalities but may be confounded by patient case mix. We explore the impact of case-mix adjustment on a publicly reported measure of early stage at diagnosis in England. METHODS: We analyzed data used for publicly reported statistics about the stage of patients diagnosed with 1 of 11 solid tumours in 2015 in England, including information on cancer site (bladder, breast, colon, rectum, kidney, lung, melanoma, non-Hodgkin lymphoma, ovarian, prostate, endometrial), age, gender, income deprivation and population-based commissioning organization. We investigated how cancer site and other patient characteristics influence organizational comparisons and attainment of early-stage targets (≥60% of all cases diagnosed in TNM stages I-II). RESULTS: Adjusting for patient case mix reduced between-organization variance by more than 50%, resulting in appreciable discordance in organizational ranks (Kendall's tau = 0.53), with 18% (37/207) of organizations being reclassified as meeting/failing the early-stage target due to case mix. CONCLUSION: Summary statistics on stage of cancer diagnosis for geographical populations currently used as public health surveillance tools to monitor organizational inequalities need to account for patient sociodemographic characteristics and cancer site case mix.Cancer Research U

Is the even distribution of insecticide-treated cattle essential for tsetse control? Modelling the impact of baits in heterogeneous environments

Background: Eliminating Rhodesian sleeping sickness, the zoonotic form of Human African Trypanosomiasis, can be achieved only through interventions against the vectors, species of tsetse (Glossina). The use of insecticide-treated cattle is the most cost-effective method of controlling tsetse but its impact might be compromised by the patchy distribution of livestock. A deterministic simulation model was used to analyse the effects of spatial heterogeneities in habitat and baits (insecticide-treated cattle and targets) on the distribution and abundance of tsetse. Methodology/Principal Findings: The simulated area comprised an operational block extending 32 km from an area of good habitat from which tsetse might invade. Within the operational block, habitat comprised good areas mixed with poor ones where survival probabilities and population densities were lower. In good habitat, the natural daily mortalities of adults averaged 6.14% for males and 3.07% for females; the population grew 8.46in a year following a 90% reduction in densities of adults and pupae, but expired when the population density of males was reduced to <0.1/km2; daily movement of adults averaged 249 m for males and 367 m for females. Baits were placed throughout the operational area, or patchily to simulate uneven distributions of cattle and targets. Gaps of 2–3 km between baits were inconsequential provided the average imposed mortality per km2 across the entire operational area was maintained. Leaving gaps 5–7 km wide inside an area where baits killed 10% per day delayed effective control by 4–11 years. Corrective measures that put a few baits within the gaps were more effective than deploying extra baits on the edges. Conclusions/Significance: The uneven distribution of cattle within settled areas is unlikely to compromise the impact of insecticide-treated cattle on tsetse. However, where areas of >3 km wide are cattle-free then insecticide-treated targets should be deployed to compensate for the lack of cattle

The presenting symptom signatures of incident cancer: evidence from the English 2018 National Cancer Diagnosis Audit

This is the final version. Available on open access from Springer Nature via the DOI in this recordData availability: Data used in this study (National Cancer Diagnosis Audit data used in this study are available through application to NHS England Data Access Request Service (DARS).Code availability: All analysis was conducted using R (version 4.1.2) and can be accessed online at https://github.com/nadine-zakkak/presenting-symptom-signatures-of-incident-cancerBACKGROUND: Understanding relationships between presenting symptoms and subsequently diagnosed cancers can inform symptom awareness campaigns and investigation strategies. METHODS: We used English National Cancer Diagnosis Audit 2018 data for 55,122 newly diagnosed patients, and examined the relative frequency of presenting symptoms by cancer site, and of cancer sites by presenting symptom. RESULTS: Among 38 cancer sites (16 cancer groups), three classes were apparent: cancers with a dominant single presenting symptom (e.g. melanoma); cancers with diverse presenting symptoms (e.g. pancreatic); and cancers that are often asymptomatically detected (e.g. chronic lymphocytic leukaemia). Among 83 symptoms (13 symptom groups), two classes were apparent: symptoms chiefly relating to cancers of the same body system (e.g. certain respiratory symptoms mostly relating to respiratory cancers); and symptoms with a diverse cancer site case-mix (e.g. fatigue). The cancer site case-mix of certain symptoms varied by sex. CONCLUSION: We detailed associations between presenting symptoms and cancer sites in a large, representative population-based sample of cancer patients. The findings can guide choice of symptoms for inclusion in awareness campaigns, and diagnostic investigation strategies post-presentation when cancer is suspected. They can inform the updating of clinical practice recommendations for specialist referral encompassing a broader range of cancer sites per symptom.Cancer Research UKInternational Alliance for Cancer Early Detectio

Using molecular data for epidemiological inference: assessing the prevalence of Trypanosoma brucei rhodesiense in Tsetse in Serengeti, Tanzania

Background: Measuring the prevalence of transmissible Trypanosoma brucei rhodesiense in tsetse populations is essential for understanding transmission dynamics, assessing human disease risk and monitoring spatio-temporal trends and the impact of control interventions. Although an important epidemiological variable, identifying flies which carry transmissible infections is difficult, with challenges including low prevalence, presence of other trypanosome species in the same fly, and concurrent detection of immature non-transmissible infections. Diagnostic tests to measure the prevalence of T. b. rhodesiense in tsetse are applied and interpreted inconsistently, and discrepancies between studies suggest this value is not consistently estimated even to within an order of magnitude. Methodology/Principal Findings: Three approaches were used to estimate the prevalence of transmissible Trypanosoma brucei s.l. and T. b. rhodesiense in Glossina swynnertoni and G. pallidipes in Serengeti National Park, Tanzania: (i) dissection/microscopy; (ii) PCR on infected tsetse midguts; and (iii) inference from a mathematical model. Using dissection/microscopy the prevalence of transmissible T. brucei s.l. was 0% (95% CI 0–0.085) for G. swynnertoni and 0% (0–0.18) G. pallidipes; using PCR the prevalence of transmissible T. b. rhodesiense was 0.010% (0–0.054) and 0.0089% (0–0.059) respectively, and by model inference 0.0064% and 0.00085% respectively. Conclusions/Significance: The zero prevalence result by dissection/microscopy (likely really greater than zero given the results of other approaches) is not unusual by this technique, often ascribed to poor sensitivity. The application of additional techniques confirmed the very low prevalence of T. brucei suggesting the zero prevalence result was attributable to insufficient sample size (despite examination of 6000 tsetse). Given the prohibitively high sample sizes required to obtain meaningful results by dissection/microscopy, PCR-based approaches offer the current best option for assessing trypanosome prevalence in tsetse but inconsistencies in relating PCR results to transmissibility highlight the need for a consensus approach to generate meaningful and comparable data

Lack of effect of lowering LDL cholesterol on cancer: meta-analysis of individual data from 175,000 people in 27 randomised trials of statin therapy

&lt;p&gt;Background: Statin therapy reduces the risk of occlusive vascular events, but uncertainty remains about potential effects on cancer. We sought to provide a detailed assessment of any effects on cancer of lowering LDL cholesterol (LDL-C) with a statin using individual patient records from 175,000 patients in 27 large-scale statin trials.&lt;/p&gt; &lt;p&gt;Methods and Findings: Individual records of 134,537 participants in 22 randomised trials of statin versus control (median duration 4.8 years) and 39,612 participants in 5 trials of more intensive versus less intensive statin therapy (median duration 5.1 years) were obtained. Reducing LDL-C with a statin for about 5 years had no effect on newly diagnosed cancer or on death from such cancers in either the trials of statin versus control (cancer incidence: 3755 [1.4% per year [py]] versus 3738 [1.4% py], RR 1.00 [95% CI 0.96-1.05]; cancer mortality: 1365 [0.5% py] versus 1358 [0.5% py], RR 1.00 [95% CI 0.93–1.08]) or in the trials of more versus less statin (cancer incidence: 1466 [1.6% py] vs 1472 [1.6% py], RR 1.00 [95% CI 0.93–1.07]; cancer mortality: 447 [0.5% py] versus 481 [0.5% py], RR 0.93 [95% CI 0.82–1.06]). Moreover, there was no evidence of any effect of reducing LDL-C with statin therapy on cancer incidence or mortality at any of 23 individual categories of sites, with increasing years of treatment, for any individual statin, or in any given subgroup. In particular, among individuals with low baseline LDL-C (&#60;2 mmol/L), there was no evidence that further LDL-C reduction (from about 1.7 to 1.3 mmol/L) increased cancer risk (381 [1.6% py] versus 408 [1.7% py]; RR 0.92 [99% CI 0.76–1.10]).&lt;/p&gt; &lt;p&gt;Conclusions: In 27 randomised trials, a median of five years of statin therapy had no effect on the incidence of, or mortality from, any type of cancer (or the aggregate of all cancer).&lt;/p&gt

New life sciences innovation and distributive justice: rawlsian goods versus senian capabilities

The successful decoding of human genome and subsequent advances in new life sciences innovation create technological presuppositions of a new possibility of justice i.e. the just distribution of both social (income, wealth, etc.) and natural (rationality, intelligence, etc.) goods. Although Rawlsians attempt to expand their theory to include this new possibility, they fail to provide plausible metrics of social justice in the genomics and post-genomics era. By contrast, Senians seem to succeed to do so through their index of basic capabilities. This paper explores what might be regarded as a Senian perspective of distributive justice in new life sciences innovation. The argument is that, by comparing freedoms (different functionings) instead of primary goods, the capability theory allows not only for the identification of injustices linked to natural lottery but also for their elimination through the use of new genomic technologies, including gene-based diagnostics, gene therapy, somatic cell engineering (SCE) and germ-line engineering (GLE). These innovative technologies seem to have the potential to reduce variability in natural goods and therefore enable individuals to convert social goods into well-being or welfare

End of life care interventions for people with dementia in care homes : addressing uncertainty within a framework for service delivery and evaluation

© 2015 Goodman et al. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedMethods: The data from three studies on EoL care in care homes: (i) EVIDEM EoL , (ii) EPOCH , and (iii) TTT EoL were used to inform the development of the framework. All used mixed method designs and two had an intervention designed to improve how care home staff provided end of life care. The EVIDEM EoL and EPOCH studies tracked the care of older people in care homes over a period of 12 months. The TTT study collected resource use data of care home residents for three months, and surveyed decedents' notes for ten months, Results: Across the three studies, 29 care homes, 528 residents, 205 care home staff, and 44 visiting health care professionals participated. Analysis of showed that end of life interventions for people with dementia were characterised by uncertainty in three key areas; what treatment is the 'right' treatment, who should do what and when, and in which setting EoL care should be delivered and by whom? These uncertainties are conceptualised as Treatment uncertainty, Relational uncertainty and Service uncertainty. This paper proposes an emergent framework to inform the development and evaluation of EoL care interventions in care homes. Conclusion: For people with dementia living and dying in care homes, EoL interventions need to provide strategies that can accommodate or "hold" the inevitable and often unresolvable uncertainties of providing and receiving care in these settingsPeer reviewe