Overdiagnosis of invasive breast cancer in population-based breast cancer screening: A short- and long-term perspective

BACKGROUND

Overdiagnosis of invasive breast cancer (BC) is a contentious issue.

OBJECTIVE

The aim of this paper is to estimate the overdiagnosis rate of invasive BC in an organised BC screening program and to evaluate the impact of age and follow-up time.

METHODS

The micro-simulation model SiMRiSc was calibrated and validated for BC screening in Flanders, where women are screened biennially from age 50 to 69. Overdiagnosis rate was defined as the number of invasive BC that would not have been diagnosed in the absence of screening per 100,000 screened women during the screening period plus follow-up time (which was set at 5 years and varied from 2 to 15 years). Overdiagnosis rate was calculated overall and stratified by age.

RESULTS

The overall overdiagnosis rate for women screened biennially from 50 to 69 was 20.1 (95%CI: 16.9-23.2) per 100,000 women screened at 5-year follow-up from stopping screening. Overdiagnosis at 5-year follow-up time was 12.9 (95%CI: 4.6-21.1) and 74.2 (95%CI: 50.9-97.5) per 100,000 women screened for women who started screening at age 50 and 68, respectively. At 2- and 15-year follow-up time, overdiagnosis rate was 98.5 (95%CI: 75.8-121.3) and 13.4 (95%CI: 4.9-21.9), respectively, for women starting at age 50, and 297.0 (95%CI: 264.5-329.4) and 34.2 (95%CI: 17.5-50.8), respectively, for those starting at age 68.

CONCLUSIONS

Sufficient follow-up time (≥10 years) after screening stops is key to obtaining unbiased estimates of overdiagnosis. Overdiagnosis of invasive BC is a larger problem in older compared to younger women.

GRADE Guidelines 30: the GRADE approach to assessing the certainty of modeled evidence-An overview in the context of health decision-making

OBJECTIVES

The objective of the study is to present the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) conceptual approach to the assessment of certainty of evidence from modeling studies (i.e., certainty associated with model outputs).

STUDY DESIGN AND SETTING

Expert consultations and an international multidisciplinary workshop informed development of a conceptual approach to assessing the certainty of evidence from models within the context of systematic reviews, health technology assessments, and health care decisions. The discussions also clarified selected concepts and terminology used in the GRADE approach and by the modeling community. Feedback from experts in a broad range of modeling and health care disciplines addressed the content validity of the approach.

RESULTS

Workshop participants agreed that the domains determining the certainty of evidence previously identified in the GRADE approach (risk of bias, indirectness, inconsistency, imprecision, reporting bias, magnitude of an effect, dose-response relation, and the direction of residual confounding) also apply when assessing the certainty of evidence from models. The assessment depends on the nature of model inputs and the model itself and on whether one is evaluating evidence from a single model or multiple models. We propose a framework for selecting the best available evidence from models: 1) developing de novo, a model specific to the situation of interest, 2) identifying an existing model, the outputs of which provide the highest certainty evidence for the situation of interest, either "off-the-shelf" or after adaptation, and 3) using outputs from multiple models. We also present a summary of preferred terminology to facilitate communication among modeling and health care disciplines.

CONCLUSION

This conceptual GRADE approach provides a framework for using evidence from models in health decision-making and the assessment of certainty of evidence from a model or models. The GRADE Working Group and the modeling community are currently developing the detailed methods and related guidance for assessing specific domains determining the certainty of evidence from models across health care-related disciplines (e.g., therapeutic decision-making, toxicology, environmental health, and health economics).

Water mediated synthesis of 6-amino-5-cyano-2-oxo-N-(pyridin-2-yl)-4-(p-tolyl)-2H-[1,2'-bipyridine]-3-carboxamide and 6-amino-5-cyano-4-(4-fluorophenyl)-2-oxo-N-(pyridin-2-yl)-2H-[1,2'-bipyridine]-3-carboxamide - An experimental and computational studies with non-linear optical (NLO) and molecular docking analyses

6-Amino-5-cyano-2-oxo-N-(pyridin-2-yl)-4-(p-tolyl)-2H-[1,2'-bipyridine]-3-carboxamide and 6-amino-5-cyano-4-(4-fluorophenyl)-2-oxo-N-(pyridin-2-yl)-2H-[1,2'-bipyridine]-3-carboxamide were synthesized through three-component reaction between N¹,N³-di(pyridin-2-yl)-malonamide, aldehyde and malononitrile in water using triethylamine as a base at room temperature. Synthesized compounds were characterized by using different techniques (FT-IR, NMR and X-ray diffraction). Additionally, the mentioned compounds were investigated by computational chemistry methods. Obtained results were supported with calculated results. Additionally, NLO properties and molecular docking analyses of related compounds were examined in detail. The binding modes of the compounds 4a and 4b were explored with the colchicine binding site of tubulin, from molecular docking studies, remarkable interactions have been observed for 4a and 4b near to the colchicines binding site of tubulin that may contribute to the inhibition of tubulin polymerization and anticancer activity.

Investigations of structural, spectral and electronic properties of enrofloxacin and boron complexes via quantum chemical calculation and molecular docking

Quantum chemical analyses were performed over enrofloxacin and boron complexes. The most stable isomer of enrofloxacin was examined at M062X/6-31+G(d) level in gas phase. Structural and spectral characterizations of enrofloxacin and its complexes were performed at same level of theory. MEP maps of studied compound were calculated via ESP charges analyses. Some quantum chemical descriptors (QCDs) were calculated to determine the non-linear optical (NLO) and biological reactivity of studied molecules. Furthermore, molecular docking calculations between boron complexes and a protein (ID: 2ITN and 2ITV) were done. ADME analyses were done in the determination of the best drug candidate. As a result, complex (3) was found as the best in the NLO applications and it was found that complex (1) and (3) have similar biological reactivity in lung cancer treatment.

Investigation of structural, electronic properties and docking calculations of some boron complexes with norfloxacin: A computational research

Quantum chemical calculations are performed over BF₂R (1), B(NO)₂R (2), B(CN)₂R (3) and B(CH₃)₂R (4) [R: 1-ethyl-6-fluoro-4-oxo-7-(piperazin-1-yl)-1,4-dihydroquinoline-3-carboxylate]. Mentioned boron complex with fluorine atoms which is BF₂R are optimized at HF/6-31+G(d), B3LYP/6-31+G(d) and M062X/6-31+G(d) level and the best level is determined by comparison of experimental and calculated results. The best calculation level is determined as M06-2X/6-31+G(d) level. The other complexes are optimized at this level. Structural properties, IR and NMR spectrum are examined in detail. Additionally, biological activities of mentioned complexes are investigated by some quantum chemical descriptors (E_HOMO, E_LUMO, I, A, E_GAP, η, σ, χ, CP, ω, N, ΔN_max and S) and molecular docking analyses. The interaction energies for complex (1), (2), (3) and (4) are calculated as -480.1, -443.6, -433.6 and -402.1 kJ mol^-1, respectively. As a result, it is found that boron complex with fluorine atoms (BF₂R) is the best candidate for anticancer drug.