Herschel dust emission as a probe of starless cores mass: MCLD 123.5+24.9 of the Polaris Flare

We present newly processed archival Herschel images of molecular cloud MCLD 123.5+24.9 in the Polaris Flare. This cloud contains five starless cores. Using the spectral synthesis code Cloudy, we explore uncertainties in the derivation of column densities, hence, masses of molecular cores from Herschel data. We first consider several detailed grain models that predict far-IR grain opacities. Opacities predicted by the models differ by more than a factor of two, leading to uncertainties in derived column densities by the same factor. Then we consider uncertainties associated with the modified blackbody fitting process used by observers to estimate column densities. For high column density clouds (N(H) $\gg$ 10$^{22}$ cm$^{-2}$), this fitting technique can underestimate column densities by about a factor of three. Finally, we consider the virial stability of the five starless cores in MCLD 123.5+24.9. All of these cores appear to have strongly sub-virial masses, assuming, as we argue, that $^{13}$CO line data provide reliable estimates of velocity dispersions. Evidently, they are not self-gravitating, so it is no surprise that they are starless.Comment: ApJ, Accepted. Minor typographical errors corrected and figures 6 & 7 updated in v

Estimating the location of the open-closed magnetic field line boundary from auroral images

The open-closed magnetic field line boundary (OCB) delimits the region of open magnetic flux forming the polar cap in the Earth’s ionosphere. We present a reliable, automated method for determining the location of the poleward auroral luminosity boundary (PALB) from far ultraviolet (FUV) images of the aurora, which we use as a proxy for the OCB. This technique models latitudinal profiles of auroral luminosity as both a single and double Gaussian function with a quadratic background to produce estimates of the PALB without prior knowledge of the level of auroral activity or of the presence of bifurcation in the auroral oval. We have applied this technique to FUV images recorded by the IMAGE satellite from May 2000 until August 2002 to produce a database of over a million PALB location estimates, which is freely available to download. From this database, we assess and illustrate the accuracy and reliability of this technique during varying geomagnetic conditions. We find that up to 35% of our PALB estimates are made from double Gaussian fits to latitudinal intensity profiles, in preference to single Gaussian fits, in nightside magnetic local time (MLT) sectors. The accuracy of our PALBs as a proxy for the location of the OCB is evaluated by comparison with particle precipitation boundary (PPB) proxies from the DMSP satellites. We demonstrate the value of this technique in estimating the total rate of magnetic reconnection from the time variation of the polar cap area calculated from our OCB estimates

Pre-referral GP consultations in patients subsequently diagnosed with rarer cancers: a study of patient-reported data.

BACKGROUND: Some patients with cancer experience multiple pre-diagnostic consultations in primary care, leading to longer time intervals to specialist investigations and diagnosis. Patients with rarer cancers are thought to be at higher risk of such events, but concrete evidence of this is lacking. AIM: To examine the frequency and predictors of repeat consultations with GPs in patients with rarer cancers. DESIGN AND SETTING: Patient-reported data on pre-referral consultations from three English national surveys of patients with cancer (2010, 2013, and 2014), pooled to maximise the sample size of rarer cancers. METHOD: The authors examined the frequency and crude and adjusted odds ratios for ≥3 (versus 1-2) pre-referral consultations by age, sex, ethnicity, level of deprivation, and cancer diagnosis (38 diagnosis groups, including 12 rarer cancers without prior relevant evidence). RESULTS: Among 7838 patients with 12 rarer cancers, crude proportions of patients with ≥3 pre-referral consultations ranged from >30.0% to 60.0% for patients with small intestine, bone sarcoma, liver, gallbladder, cancer of unknown primary, soft-tissue sarcoma, and ureteric cancer. The range was 15.0-30.0% for patients with oropharyngeal, anal, parotid, penile, and oral cancer. The overall proportion of responders with any cancer who had ≥3 consultations was 23.4%. Multivariable logistic regression indicated concordant patterns, with strong evidence for variation between rarer cancers (P <0.001). CONCLUSION: Patients with rarer cancers experience pre-referral consultations at frequencies suggestive of middle-to-high diagnostic difficulty. The findings can guide the development of new diagnostic interventions and 'safety-netting' approaches for symptomatic presentations encountered in patients with rarer cancers.This work was supported by a Cancer Research UK Clinician Scientist Fellowship (A18180) to GL.This is the final version of the article. It first appeared from the British Journal of General Practice via http://dx.doi.org/10.3399/bjgp16X68397

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

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

A retrospective cohort study assessing patient characteristics and the incidence of cardiovascular disease using linked routine primary and secondary care data

This is the final version. Available from the publisher via the DOI in this record.Objectives: Data linkage combines information from several clinical data sets. The authors examined whether coding inconsistencies for cardiovascular disease between components of linked data sets result in differences in apparent population characteristics. Design: Retrospective cohort study. Setting: Routine primary care data from 40 Scottish general practitioner (GP) surgeries linked to national hospital records. Participants: 240 846 patients, aged 20 years or older, registered at a GP surgery. Outcomes: Cases of myocardial infarction, ischaemic heart disease and stroke (cerebrovascular disease) were identified from GP and hospital records. Patient characteristics and incidence rates were assessed for all three clinical outcomes, based on GP, hospital, paired GP/hospital (similar diagnoses recorded simultaneously in both data sets) or pooled GP/hospital records (diagnosis recorded in either or both data sets). Results: For all three outcomes, the authors found evidence (p<0.05) of different characteristics when using different methods of case identification. Prescribing of cardiovascular medicines for ischaemic heart disease was greatest for cases identified using paired records (p≤0.013). For all conditions, 30-day case fatality rates were higher for cases identified using hospital compared with GP or paired data, most noticeably for myocardial infarction (hospital 20%, GP 4%, p=0.001). Incidence rates were highest using pooled GP/hospital data and lowest using paired data. Conclusions: Differences exist in patient characteristics and disease incidence for cardiovascular conditions, depending on the data source. This has implications for studies using routine clinical data

Post-sampling mortality and non-response patterns in the English Cancer Patient Experience Survey: Implications for epidemiological studies based on surveys of cancer patients.

BACKGROUND: Surveys of the experience of cancer patients are increasingly being introduced in different countries and used in cancer epidemiology research. Sampling processes, post-sampling mortality and survey non-response can influence the representativeness of cancer patient surveys. METHODS: We examined predictors of post-sampling mortality and non-response among patients initially included in the sampling frame of the English Cancer Patient Experience Survey. We also compared the respondents' diagnostic case-mix to other relevant populations of cancer patients, including incident and prevalent cases. RESULTS: Of 109,477 initially sampled cancer patients, 6273 (5.7%) died between sampling and survey mail-out. Older age and diagnosis of brain, lung and pancreatic cancer were associated with higher risk of post-sampling mortality. The overall response rate was 67% (67,713 respondents), being >70% for the most affluent patients and those diagnosed with colon or breast cancer and <50% for Asian or Black patients, those under 35 and those diagnosed with brain cancer. The diagnostic case-mix of respondents varied substantially from incident or prevalent cancer cases. CONCLUSIONS: Respondents to the English Cancer Patient Experience Survey represent a population of recently treated cancer survivors. Although patient survey data can provide unique insights for improving cancer care quality, features of survey populations need to be acknowledged when analysing and interpreting findings from studies using such data.The authors wish to thank the Department of Health as the principal investigator of the 2010 Cancer Patient Experience Survey, Quality Health as the data collector and for making available the anonymous sampling frame, and all the National Health Service Acute Trusts in England who supported the survey. GL is supported by a Cancer Research UK Clinician Scientist Fellowship (A18180). The views expressed in this publication are those of the authors and not necessarily those of any funder or any other organisation or institution.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.canep.2015.12.01

What explains worse patient experience in London? Evidence from secondary analysis of the Cancer Patient Experience Survey.

OBJECTIVE: To explore why patients with cancer treated by London hospitals report worse experiences of care compared with those treated in other English regions. DESIGN: Secondary analysis of the 2011/2012 National Cancer Patient Experience Survey (n=69 086). SETTING AND PARTICIPANTS: Patients with cancer treated by the English National Health Service (NHS) hospitals. MAIN OUTCOME MEASURES: 64 patient experience measures covering all aspects of cancer care (pre-diagnosis to discharge). METHODS: Using mixed effects logistic regression, we explored whether poorer scores in London hospitals could be explained by patient case-mix (age, gender, ethnicity and cancer type). Because patients referred to tertiary centres and/or with complex medical problems may report more critical experiences, we also explored whether the experiences reported in London may reflect higher concentration of teaching hospitals in the capital. Finally, using the data from the (general) Adult Inpatients Survey, we explored whether the extent of poorer experience reported by London patients was similar for respondents to either survey. RESULTS: For 52/64 questions, there was evidence of poorer experience in London, with the percentage of patients reporting a positive experience being lower compared with the rest of England by a median of 3.7% (IQR 2.5-5.4%). After case-mix adjustment there was still evidence for worse experience in London for 45/64 question [corrected]. In addition, adjusting for teaching hospital status made trivial difference to the case-mix-adjusted findings. There was evidence that London versus rest-of-England differences were greater for patients with cancer compared with (general) hospital inpatients for 10 of 16 questions in both the Cancer Patient Experience and the Adult Inpatients Surveys. CONCLUSIONS: Patients with cancer treated by London hospitals report worse care experiences and by and large these differences are not explained by patient case-mix or teaching hospital status. Efforts to improve care in London should aim to meet patient expectations and improve care quality.This work was supported by funding from the European Community Seventh Framework Programme under grant agreement 223175 (HEALTH-F2_2009-223175). The funding source had no role in the writing of this report or the decision to submit the paper for publication for which all authors had responsibility. All authors except PP and NP are employed by the PHG Foundation, which is the working name of the Foundation for Genomics and Population Health, a charitable company registered in England and Wales, charity No. 1118664 company No. 5823194

Beyond the ecological fallacy: potential problems when studying healthcare organisations.

Ecological studies, which consider patient groups rather than individuals, are common in health policy research. The ‘ecological fallacy’ is a well-recognised methodological concern, but in this perspectives paper, we focus on less often appreciated but equally important limitations of such studies. In particular, we consider reliability and power as they apply to ecological studies, and make recommendations to inform the appropriate design and interpretation of these increasingly popular studies.This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. GL is supported by a Cancer Research UK Clinician Scientist Fellowship (A18180). The views expressed in this publication are those of the authors and not necessarily those of any funder or any other organisation or institution.This is the author accepted manuscript. The final version is available from SAGE via http://dx.doi.org/10.1177/014107681561057

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

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

Response rates to patient surveys

BACKGROUND: Patient surveys typically have variable response rates between organizations, leading to concerns that such differences may affect the validity of performance comparisons. OBJECTIVE: To explore the size and likely sources of associations between hospital-level survey response rates and patient experience. RESEARCH DESIGN, SUBJECTS, AND MEASURES: Cross-sectional mail survey including 60 patient experience items sent to 101,771 cancer survivors recently treated by 158 English NHS hospitals. Age, sex, race/ethnicity, socioeconomic status, clinical diagnosis, hospital type, and region were available for respondents and nonrespondents. RESULTS: The overall response rate was 67% (range, 39% to 77% between hospitals). Hospitals with higher response rates had higher scores for all items (Spearman correlation range, 0.03-0.44), particularly questions regarding hospital-level administrative processes, for example, procedure cancellations or medical note availability.From multivariable analysis, associations between individual patient experience and hospital-level response rates were statistically significant (P<0.05) for 53/59 analyzed questions, decreasing to 37/59 after adjusting for case-mix, and 25/59 after further adjusting for hospital-level characteristics.Predicting responses of nonrespondents, and re-estimating hypothetical hospital scores assuming a 100% response rate, we found that currently low performing hospitals would have attained even lower scores. Overall nationwide attainment would have decreased slightly to that currently observed. CONCLUSIONS: Higher response rate hospitals have more positive experience scores, and this is only partly explained by patient case-mix. High response rates may be a marker of efficient hospital administration, and higher quality that should not, therefore, be adjusted away in public reporting. Although nonresponse may result in slightly overestimating overall national levels of performance, it does not appear to meaningfully bias comparisons of case-mix-adjusted hospital results.GL is supported by a Cancer Research UK Clinician Scientist Fellowship (A18180).This is the final version of the article. It first appeared from Wolters Kluwer via http://dx.doi.org/10.1097/MLR.000000000000045