No abstract

An empirical model of joint decisions of where to live and where to work demonstrates that individuals make residential and job location choices by trading off wages, housing prices, and commuting costs. Wages are higher in metropolitan markets, but housing prices are also higher in urban areas. Consumers can live in lower priced nonmetropolitan houses and still earn urban wages, but they incur commuting costs that increase with distance from the city. Improvements in transportation that lower commuting time will increase nonmetropolitan populations and will increase the number of nonmetropolitan commuters to metropolitan markets. Equal wage growth across labor markets causes a shift in relative population from rural to urban markets, while an equiproportional increase in housing prices causes a population shift toward rural areas.

Background:The objective of this study is to construct a preoperative nomogram predicting lymph node metastasis (LNM) in early-cervical cancer patients.Methods:Between 2009 and 2012, 493 early-cervical cancer patients received hysterectomy and pelvic/para-aortic lymphadenectomy. Patients who were diagnosed during 2009–2010 were assigned to a model-development cohort (n=304) and the others were assigned to a validation cohort (n=189). A multivariate logistic model was created from preoperative clinicopathologic data, from which a nomogram was developed and validated. A predicted probability of LNM<5% was defined as low risk.Results:Age, tumour size assessed by magnetic resonance imaging, and LNM assessed by positron emission tomography/computed tomography were independent predictors of nodal metastasis. The nomogram incorporating these three predictors demonstrated good discrimination and calibration (concordance index=0.878; 95% confidence interval (CI), 0.833−0.917). In the validation cohort, the discrimination accuracy was 0.825 (95% CI, 0.736−0.895). In the model-development cohort, 34% of them were classified as low risk and negative predictive value (NPV) was 99.0%. In the validation cohort, 38% were identified as low risk and NPV was 95.8%. Integrating the model-development and validation cohorts, negative likelihood ratio was 0.094 (95% CI, 0.036−0.248).Conclusion:A robust nomogram predicting LNM in early cervical cancer was developed. This model may improve clinical trial design and help physicians to decide whether lymphadenectomy should be performed.