Long-term prognostic significance of HER-2/neu in untreated node-negative breast cancer depends on the method of testing

INTRODUCTION: The prognostic significance of HER-2/neu in breast cancer is a matter of controversy. We have performed a study in 101 node-negative breast cancer patients with long-term follow-up not treated in the adjuvant setting, and analysed the prognostic significance of immunohistochemistry (IHC) and fluorescence in situ hybridisation (FISH), both separately and in combination, in comparison with traditional prognostic factors. METHODS: Overexpression was classified semiquantitatively according to a score (0 to 3+) (HER-2_SCO). FISH was used to analyse HER2/neu amplification (HER-2_AMP). Patients classified 2+ by IHC were examined with FISH for amplification (HER-2_ALG). Patients with 3+ overexpression as well as amplification of HER-2/neu were positive for the combined variable HER2_COM. These variables were compared with tumour size, histological grade and hormone receptor status. RESULTS: HER-2_SCO was 3+ in 20% of all tumours. HER-2_ALG was positive in 22% and amplification (HER-2_AMP) was found in 17% of all tumours. Eleven percent of the tumours showed simultaneous 3+ overexpression and amplification. Only histological grade (relative risk [RR] 3.22, 95% confidence interval [CI] 1.73–5.99, P = 0.0002) and HER-2_AMP (RR 2.47, 95% CI 1.12–5.48, P = 0.026) were significant for disease-free survival in multivariate analysis. For overall survival, both histological grade (RR 3.89, 95% CI 1.77–8.55, P = 0.0007) and HER-2_AMP (RR 3.08, 95% CI 1.24–7.66, P = 0.016) retained their independent significance. CONCLUSION: The prognostic significance of HER-2/neu in node-negative breast cancer depends on the method of testing: only the amplification of HER-2/neu is an independent prognostic factor for the long-term prognosis of untreated node-negative breast cancer

Endogeneity in Panel Data Models with Time-Varying and Time-Fixed Regressors: To IV or Not IV?

We analyse the problem of parameter inconsistency in panel data econometrics due to the correlation of exogenous variables with the error term. A common solution in this setting is to use Instrumental-Variable (IV) estimation in the spirit of Hausman-Taylor (1981). However, some potential shortcomings of the latter approach recently gave rise to the use of non-IV two-step estimators. Given their growing number of empirical applications, we aim to systematically compare the performance of IV and non-IV approaches in the presence of time-fixed variables and right hand side endogeneity using Monte Carlo simulations, where we explicitly control for the problem of IV selection in the Hausman-Taylor case. The simulation results show that the Hausman- Taylor model with perfect-knowledge about the underlying data structure (instrument orthogonality) has on average the smallest bias. However, compared to the empirically relevant specification with imperfect-knowledge and instruments chosen by statistical criteria, the non-IV rival performs equally well or even better especially in terms of estimating variable coefficients for time- fixed regressors. Moreover, the non-IV method tends to have a smaller root mean square error (rmse) than both Hausman-Taylor models with perfect and imperfect knowledge about the underlying correlation between r.h.s variables and residual term. This indicates that it is generally more efficient. The results are roughly robust for various combinations in the time and cross-section dimension of the data

EU Structural Funds and Regional Income Convergence A Sobering Experience

The European Structural and Investment Funds (ESIF) are the prime instrument of EU regional policy. European policy makers place considerable hope into their growth stimulating funding measures to overcome current economic stagnation. Consequently, there is a strong need for credible evidence regarding the programs' effectiveness. Based on an empirical identification strategy linked to modern growth theory, we find that the disbursement of EU structural funds is negatively correlated with regional growth. Incorporating spatial dynamics and decomposing this correlation into a direct and a spatially-indirect component, it is particularly the latter which determines this 'sobering' finding. Regarding the economics behind these results, the obtained negative spatial effect may reflect the role played by policy-induced spatial competition among neighboring regions. It could also highlight the backwardness in technological endowment and economic structures of highly funded regions. In any case, EU structural funding does not seem to contribute effectively to foster income convergence across regions.Die europäischen Struktur und Investmentfonds (ESIF) sind das wichtigste Instrument der EU-Regionalpolitik; die europäische Politik setzt große Hoffnungen in die wachstumsstimulierende Wirkung dieser Fördermaßnahmen zur Überwindung der aktuellen wirtschaftlichen Stagnation. Basierend auf einer empirischen Identifikationsstrategie können in diesem Papier keine Belege für positive Förderwirkungen gefunden werden. Werden räumliche Strukturen berücksichtigt, zeigt sich, dass räumlich indirekte Effekte dieses Ergebnis beeinflussen - also solche Regionen weniger wachsen, deren Nachbarn stark gefördert werden. Neben der potenziellen Erklärung, dass Nachbarn gegenseitig ihre Investoren abwerben, legt dieses Resultat nahe, dass hochgeförderte regionale Cluster unter struktureller und technologischer Rückständigkeit leiden, die durch Wachstumsprogramme nicht überwunden werden. Beide möglichen Erklärungen lassen den Schluss zu, dass die Förderung ihr eigentliches Ziel, die Konvergenz der Regionen, verfehlt

Measurement of CP asymmetries in D± → η′π± and Ds±→η′π± decays

A search for CP violation in D±→η′π± and Ds±→η′π± decays is performed using proton–proton collision data, corresponding to an integrated luminosity of 3 fb−1, recorded by the LHCb experiment at centre-of-mass energies of 7 and 8 TeV. The measured CP-violating charge asymmetries are ACP(D±→η′π±)=(−0.61±0.72±0.53±0.12)% and ACP(Ds±→η′π±)=(−0.82±0.36±0.22±0.27)%, where the first uncertainties are statistical, the second systematic, and the third are the uncertainties on the ACP(D±→KS0π±) and ACP(Ds±→φπ±) measurements used for calibration. The results represent the most precise measurements of these asymmetries to date