Exploring Uncertainty in Canine Cancer Data Sources Through Dasymetric Refinement

In spite of the potentially groundbreaking environmental sentinel applications, studies of canine cancer data sources are often limited due to undercounting of cancer cases. This source of uncertainty might be further amplified through the process of spatial data aggregation, manifested as part of the modifiable areal unit problem (MAUP). In this study, we explore potential explanatory factors for canine cancer incidence retrieved from the Swiss Canine Cancer Registry (SCCR) in a regression modeling framework. In doing so, we also evaluate differences in statistical performance and associations resulting from a dasymetric refinement of municipal units to their portion of residential land. Our findings document severe underascertainment of cancer cases in the SCCR, which we linked to specific demographic characteristics and reduced use of veterinary care. These explanatory factors result in improved statistical performance when computed using dasymetrically refined units. This suggests that dasymetric mapping should be further tested in geographic correlation studies of canine cancer incidence and in future comparative studies involving human cancers

Mastectomy or breast conserving surgery? Factors affecting type of surgical treatment for breast cancer – a classification tree approach

BACKGROUND: A critical choice facing breast cancer patients is which surgical treatment – mastectomy or breast conserving surgery (BCS) – is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of "propensity" is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process. METHODS: Data was extracted from the WA Cancer Registry on women diagnosed with breast cancer in WA from 1990 to 2000. Subjects' treatment preferences were predicted from covariates using both classification trees and logistic regression. RESULTS: Tumor size was the primary determinant of patient choice, subjects with tumors smaller than 20 mm in diameter preferring BCS. For subjects with tumors greater than 20 mm in diameter factors such as patient age, nodal status, and tumor histology become relevant as predictors of patient choice. CONCLUSION: Classification trees perform as well as logistic regression for predicting patient choice, but are much easier to interpret for clinical use. The selected tree can inform clinicians' advice to patients

Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss Canine Cancer Registry

Epidemiological research of canine cancers could inform comparative studies of environmental determinants for a number of human cancers. However, such an approach is currently limited because canine cancer data sources are still few in number and often incomplete. Incompleteness is typically due to under-ascertainment of canine cancers. A main reason for this is because dog owners commonly do not seek veterinary care for this diagnosis. Deeper knowledge on under-ascertainment is critical for modeling canine cancer incidence, as an indication of zero incidence might originate from the sole absence of diagnostic examinations within a given sample unit. In the present case study, we investigated effects of such structural zeros on models of canine cancer incidence. In doing so, we contrasted two scenarios for modeling incidence data retrieved from the Swiss Canine Cancer Registry. The first scenario was based on the complete enumeration of incidence data for all Swiss municipal units. The second scenario was based on a filtered sample that systematically discarded structural zeros in those municipal units where no diagnostic examination had been performed. By means of cross-validation, we assessed and contrasted statistical performance and predictive power of the two modelling scenarios. This analytical step allowed us to demonstrate that structural zeros impact on the generalizability of the model of canine cancer incidence, thus challenging future comparative studies of canine and human cancers. The results of this case study show that increased awareness about the effects of structural zeros is critical to epidemiological research

Molecular homology between canine spontaneous oral squamous cell carcinomas and human head-and-neck squamous cell carcinomas reveals disease drivers and therapeutic vulnerabilities

Spontaneously occurring canine oral squamous cell carcinomas (COSCC) are viewed as a useful model for human head and neck squamous cell carcinomas (HNSCC). To date however, the molecular basis of COSCC remains poorly understood. To identify changes pertinent to cancer cells in COSCC, we specifically analyzed tumor cells and matched normal epithelium from clinical formalin-fixed paraffin-embedded specimens using laser-capture-microdissection coupled with RNA-sequencing (RNAseq). Our results identify strong contributions of epithelial-to-mesenchymal transition (EMT), classical tumor-promoting (such as E2F, KRAS, MYC, mTORC1, and TGFB1 signaling) and immune-related pathways in the tumor epithelium of COSCC. Comparative analyses of COSCC with 43 paired tumor/normal HNSCC from The Cancer Genome Atlas revealed a high homology in transcriptional reprogramming, and identified processes associated with cell cycle progression, immune processes, and loss of cellular differentiation as likely central drivers of the disease. Similar to HNSCC, our analyses suggested a ZEB2-driven partial EMT in COSCC and identified selective upregulation of KRT14 and KRT17 in COSCC. Beyond homology in transcriptional signatures, we also found therapeutic vulnerabilities strongly conserved between the species: these included increased expression of PD-L1 and CTLA-4, coinciding with EMT and revealing the potential for immune checkpoint therapies, and overexpression of CDK4/6 that sensitized COSCC to treatment with palbociclib. In summary, our data significantly extend the current knowledge of molecular aberrations in COSCC and underline the potential of spontaneous COSCC as a model for HNSCC to interrogate therapeutic vulnerabilities and support translation of novel therapies from bench to bedside

Finanzierung in der MEM-Industrie: gut mit Verbesserungspotenzial

Haben es KMU in der Maschinen-, Elektro- und Metallindustrie schwerer, an Bankkredite zu kommen? Eine Studie sagt: Der Zugang sei gewährleistet, doch die Bonitätsprüfung ausgeprägter. Mit spezifischeren Strategien könnten die Firmen ihre Finanzierungssituation aber noch verbessern

Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss Canine Cancer Registry

Epidemiological research of canine cancers could inform comparative studies of environmental determinants for a number of human cancers. However, such an approach is currently limited because canine cancer data sources are still few in number and often incomplete. Incompleteness is typically due to under-ascertainment of canine cancers. A main reason for this is because dog owners commonly do not seek veterinary care for this diagnosis. Deeper knowledge on under-ascertainment is critical for modelling canine cancer incidence, as an indication of zero incidence might originate from the sole absence of diagnostic examinations within a given sample unit. In the present case study, we investigated effects of such structural zeros on models of canine cancer incidence. In doing so, we contrasted two scenarios for modelling incidence data retrieved from the Swiss Canine Cancer Registry. The first scenario was based on the complete enumeration of incidence data for all Swiss municipal units. The second scenario was based on a filtered sample that systematically discarded structural zeros in those municipal units where no diagnostic examination had been performed. By means of cross-validation, we assessed and contrasted statistical performance and predictive power of the two modelling scenarios. This analytical step allowed us to demonstrate that structural zeros impact on the generalisability of the model of canine cancer incidence, thus challenging future comparative studies of canine and human cancers. The results of this case study show that increased awareness about the effects of structural zeros is critical to epidemiological research

Exploring uncertainty in canine cancer data sources through dasymetric refinement

In spite of the potentially groundbreaking environmental sentinel applications, studies of canine cancer data sources are often limited due to undercounting of cancer cases. This source of uncertainty might be further amplified through the process of spatial data aggregation, manifested as part of the modifiable areal unit problem (MAUP). In this study, we explore potential explanatory factors for canine cancer incidence retrieved from the Swiss Canine Cancer Registry (SCCR) in a regression modeling framework. In doing so, we also evaluate differences in statistical performance and associations resulting from a dasymetric refinement of municipal units to their portion of residential land. Our findings document severe underascertainment of cancer cases in the SCCR, which we linked to specific demographic characteristics and reduced use of veterinary care. These explanatory factors result in improved statistical performance when computed using dasymetrically refined units. This suggests that dasymetric mapping should be further tested in geographic correlation studies of canine cancer incidence and in future comparative studies involving human cancers.</p

Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss canine cancer registry

Epidemiological research of canine cancers could inform comparative studies of environmental determinants for a number of human cancers. However, such an approach is currently limited because canine cancer data sources are still few in number and often incomplete. Incompleteness is typically due to under-ascertainment of canine cancers. A main reason for this is because dog owners commonly do not seek veterinary care for this diagnosis. Deeper knowledge on under-ascertainment is critical for modelling canine cancer incidence, as an indication of zero incidence might originate from the sole absence of diagnostic examinations within a given sample unit. In the present case study, we investigated effects of such structural zeros on models of canine cancer incidence. In doing so, we contrasted two scenarios for modelling incidence data retrieved from the Swiss Canine Cancer Registry. The first scenario was based on the complete enumeration of incidence data for all Swiss municipal units. The second scenario was based on a filtered sample that systematically discarded structural zeros in those municipal units where no diagnostic examination had been performed. By means of cross-validation, we assessed and contrasted statistical performance and predictive power of the two modelling scenarios. This analytical step allowed us to demonstrate that structural zeros impact on the generalisability of the model of canine cancer incidence, thus challenging future comparative studies of canine and human cancers. The results of this case study show that increased awareness about the effects of structural zeros is critical to epidemiological research.</p