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[This corrects the article DOI: 10.1371/journal.pone.0204559.].

Objectives The healthy worker survivor effect (HWSE) is a well-recognised bias usually described as a form of selection bias or confounding. A more precise epidemiologic explanation, however, has been elusive. We distinguish several components of the HWSE and suggest methods for bias correction in occupational cohort studies. Method Although generally referred to a single effect, we demonstrate using simulation studies that there are in fact four distinct aspects of the HWSE. Two aspects, (1) time-varying confounding by variables on the causal pathway and (2) heterogeneity in susceptibility, are functions of the underlying process of the exposure and disease under study. The other two, (3) left truncation and (4) right truncation, are functions of how the data are collected, ie the study design. We quantify the bias induced by each aspect of HWSE on dose-response parameter estimates and apply methods designed to reduce the bias. Results We find that causal techniques, eg, g-estimation and IPTW, can correct for time-varying confounding. Heterogeneous susceptibility in combination with either left or right truncationcan be corrected using inverse probability of censoring weights. The health related variables needed to make either of these methods succeed in reducing the bias are often unmeasured. Conclusions HWSE occurs due to the presence of any of four factors that may function separately or in concert to produce a downward bias if not accounted for. We provide guidance for methodologic approaches to reduce the bias.

This special issue presents research on the role of digital health and communication technologies in later life. Drawing from the observation that people’s longer lives are affected by digital technologies to varying extents and recognizing the vast supply of traditional and digital technologies targeted at older users, we maintain that the principle of aged heterogeneity also manifests itself with respect to the adoption and use of digital technologies. Basing on the findings presented in the articles of the issue, we conclude n this introduction to the issue that the concept of aged heterogeneity and the particularities of old age as a stage of life are still insufficiently incorporated into the design of digital technologies and applications.

Ovarian cancer encompasses a collection of neoplasms with distinct clinicopathological and molecular features and prognosis. Despite there being a variety of ovarian cancer subtypes, these are treated as a single disease. Tremendous efforts have been made to characterize these subtypes and identify tumoral pathways and potential biomarkers for therapeutic strategies. As in other cancer types, tumor heterogeneity appears to be very high across subtypes and within a single tumor, representing a major cause of treatment failure. We describe the morphological and molecular heterogeneity among ovarian cancers and discuss recent advances in our understanding of intratumor heterogeneity.

Gastric cancer (GC) represents a global health concern. Despite advances in prevention, diagnosis, and therapy, GC is still the third leading cause of cancer mortality worldwide, with more than 720,000 estimated deaths in 2012. Overall survival for advanced disease is about 1 year, a dismal prognosis that is partly due to the high levels of biological heterogeneity found in GC. Indeed, GC is a highly heterogeneous disease from morphological and molecular standpoints. The numerous histological and molecular classifications currently available reflect such heterogeneity. Although recent high-throughput studies cluster the molecular data obtained into subgroups with clinical relevance, we still need a practical, prognostic, and predictive classification system, integrating morphological and molecular features, towards the identification of novel therapeutic targets. It is noteworthy that GC heterogeneity encompasses not only interpatient variability (intertumour heterogeneity), but also variations within the same tumour (intratumour heterogeneity). The latter encompasses spatial heterogeneity (in different tumour areas) and temporal heterogeneity (along progression from primary to recurrent and/or metastatic disease). In this review, we analyse the morphological, immunophenotypic, and molecular heterogeneity in GC as the basis for a better understanding of the disease, and discuss the practical implications for diagnostic pathology, prognostic evaluation, and precision therapy.

Background Diuretics are used in premature babies with chronic lung disease despite minimal evidence. The aim of this study was to assess the use of diuretics in neonatal units in England. Method An electronic survey using Survey Monkey was sent to 108 units in the Medicines for Children Research Network Neonatal Network. Results There were 66 responses with useable data from 55 unique units. 20% had a protocol for use. 49% would consider starting diuretics after 5 weeks of age and half would start diuretics in situations such as being unable to wean ventilation, unable to extubate, unable to wean off CPAP, chronic lung disease and chronic lung disease in the presence of a PDA. 70% had no rule when to stop diuretics, 22% stopped off supplemental oxygen and 8% off CPAP. 48% use chlorthiazide plus spironolactone in babies who are fully fed and 84% prefer furosemide in babies requiring intravenous treatment. Table 1 shows the variation in the doses within diuretics. Abstract 606 Table 1 Dose (mg/kg) Frequency (Hours) Total daily dose (mg/kg/24h) Median Min - Max Median Min - Max Median Min - Max Furosemide 1 0.5–3 12 6–24 2 1–4 Spironolactone 1 0.5–10 12 12–24 2 1–20 Chlorthiazide 10 1–25 12 12–24 20 2–50 Hydrochlorthiazide 15 10–20 12 12 30 20–40 Conclusions There is wide heterogeneity in the use of diuretics in England. The majority use chlorthiazide plus spironolactone in babies who are fed and furosemide intravenously.

Introduction Prematurity is a leading cause of neonatal morbidity and mortality. Tests are available to help predict the likelihood of pre-term labour (PTL), although optimal protocols remain uncertain. We assessed the changing pattern of testing in English maternity units. Methods 163 maternity units were surveyed online in Sept/Oct 2011, and again in Sept/Oct 2012. In 2012, non-responders were followed up by telephone contact. The overall response rate improved from 32.5% (54 units) in 2011 to 73% (119 units) in 2012. Data were analysed quantitatively using contingency tables, and spatially using Geomapping software. Results In 2012, 87% (CI; 80–92%) of units used biochemical testing to predict PTL, a significant (p < 0.05) increase from 2011 (76%, CI; 63–85%). For units where data were available for both years, 33% altered their method of PTL testing between 2011–2012, with 40% of these initiating biochemical testing. 14 units did not test for pre-term labour (11%, CI; 7–18%). The most commonly cited barriers to testing were cost and inexperience of operators, each cited by 16% of units (CI; 10–24%). On the basis of test results, 94% (C1; 87–97) of units gave steroids, but only 77% (CI; 67–84) discharged home and 82% (CI; 73–88%) arranged in utero transfer. Conclusions Our results suggest a heterogeneous pattern of test utilisation. The high proportion of units changing methods within a year implies confusion regarding optimal strategies for PTL prediction. There is an urgent need for further research and clearer guidance in this area. Heterogeneity in protocols could lead to suboptimal allocation of valuable neonatal network resources.

The intrinsic complexity, variety of concepts and numerous ways to quantify landscape heterogeneity (LH) may hamper a better understanding of how its components relate to ecological phenomena. Our study is the first to synthesize understanding of this concept and to provide the state of the art on the subject based on a comprehensive systematic literature review of 661 articles published between 1982 and 2019. Definitions, terminologies and measurements of LH were diverse and conflicting. Most articles (534 out of 661) did not provide any definition for LH, and we found great variation among the studies that did. According to our review, only 10 studies measured the effects of different land-cover types on biotic or abiotic processes (functional LH). The remaining 651 studies measured physical attributes of the landscape without mentioning that different land-cover types may impact biotic and abiotic processes differently (structural LH). The metrics most frequently used to represent LH were the Shannon diversity index and proportion of land-cover type. Most metrics used as proxies of LH also coincided with those used to represent non-heterogeneity metrics, such as fragmentation and connectivity. We identify knowledge gaps, indicate future perspectives and propose guidelines that should be addressed when researching LH.