Résumé
Objective@#To explore the value of the constructed prognostic prediction model of resectable lung cancer in predicting the survival and prognosis of patients.@*Methods@#A total of 2 267 patients with primary lung cancer in Shanxi Provincial Cancer Hospital from January 2007 to September 2018 were selected. All patients underwent primary lung cancer surgery without a second primary tumor. Gender, age, occupation, tumor site, pathological type, surgical path, surgical method, tumor stage and treatment were selected as the prognostic factors. A Cox proportional hazard model was used to construct a prognostic index (PI) equation to calculate the PI value of each patient. According to the different ranges of PI values, the low-, intermediate- and high-risk prognosis groups were divided, and the survival status of three groups were evaluated.@*Results@#Gender (RR= 0.684, P= 0.001), age (RR= 0.591, P < 0.01), occupation (RR= 1.439, P= 0.001), pathological type (RR= 3.694, P < 0.01), surgical path (RR= 0.734, P= 0.001), tumor stage (RR= 0.352, P= 0.007) were independent factors affecting the prognosis of patients with resectable lung cancer. Female, ≤65 years old, thoracoscopic surgery, and tumor stage Ⅰ were prognostic protective factors, and their risks of poor prognosis were reduced by 31.6%, 40.9%, 26.6%, and 64.8%, respectively. Farmer and adenosquamous carcinoma were prognostic risk factors, and their risks of poor prognosis were increased by 43.9% and 269.4%, respectively. The PI equation was ∑βixi=-0.380 X1-0.526 X2+0.364 X31+1.307 X55-0.309 X6-1.045 X81 (X1 was the gender, X2 was the age, X31 was the occupation as a farmer, X55 was the pathological type of adenosquamous carcinoma, X6 was the surgical path, X81 was the tumor stage Ⅰ). PI <-1 was the low-risk group, PI ≥-1 and ≤-0.5 was the intermediate-risk group, PI >-0.5 was the high-risk group, and the differences of their survival rates were statistically significant (P < 0.05). The 1-, 3-, and 5-year survival rates for the low-, risk groups were 96.8%, 87.0% and 77.9%; the intermediate-risk group were 91.8%, 82.2% and 61.7%; the high-risk group were 86.5%, 61.7% and 50.3%. respectively.@*Conclusion@#The prognostic prediction model of resectable lung cancer can predict the prognosis risk and the corresponding survival rate of patients with resectable lung cancer, and it can help clinicians to evaluate the prognosis and formulate subsequent treatment plans.
Résumé
Objetivo. Evaluar diferentes modelos matemáticos aplicados a las curvas de lactancia, establecer cuál de ellos presenta el mejor ajuste y estimar los parámetros genéticos para las características derivadas del mejor modelo. Materiales y métodos. Se empleó la información de 426797 registros de control lechero mensual de 49108 vacas Holstein de 470 hatos de los departamentos de Cundinamarca, Antioquia, Valle, Boyacá, Nariño y Cauca. Fueron evaluados los modelos matemáticos no lineales propuestos por Wood, Brody, Wilmink y Papajcsik y Bodero. Luego de seleccionar el modelo que mejor ajustó las curvas de lactancia, se estimaron los parámetros genéticos para las características (βo), producción de leche al pico (y max), tiempo al pico (t pico) y producción total a los 305 días (P305) donde se emplearon los efectos fijos de zona, parto y grupo contemporáneo. Resultados. El modelo de Wood presentó valores altos de PAIC y PBIC y valores altos de R². En las características bo, y max, t pico y P305, derivadas del modelo de Wood, el valor promedio fue de 16.64±6.34 lt, 27.39±6.85 lt, 44.55 ± 13.19 días y 6212 ± 1690 lt, respectivamente. Las características βo y t pico presentaron una heredabilidad baja (0.02) y las características y max y P305 presentaron una heredabilidad de baja a media (0.15 y 0.17, respectivamente). Conclusiones. El modelo que mejor ajusta las curvas de lactancia en bovinos Holstein es el modelo de Wood. Las heredabilidades medias y la alta correlación genética entre y max y P305, indican que es posible incluirlas en programas de selección.
Objective. Evaluate different mathematical models applied to lactation curves, determine which of them represent the best fit and estimate genetic parameters for the characteristics derived from the best model. Materials and methods. Information from 426797 monthly milk control records was used from 49108 Holstein cows coming from 470 dairy herds located in Cundinamarca, Antioquia, Valle, Boyacá, Nariño and Cauca. Nonlinear mathematical models proposed by Wood, Brody, Wilmink and Papajcsik and Bodero were evaluated. After selecting the model that best adjusted the lactation curves, genetic parameters were estimated for the characteristics (βo), peak milk production (y max), time to peak (t pico) and total production at 305 days (P305) where the fixed area effects, delivery and contemporary group were used. Results. Wood's model showed high values of PAIC and PBIC and high values of R². In relation to bo, y max, t pico y P305 characteristics, derived from the Wood model, the average value was 16.64 ± 6.34 lt, 27.39 lt ± 6.85, 44.55 ± 13.19 days and 6212 ± 1690 lt, respectively. βo y t pico characteristics presented a low heritability (0.02) and the y max and P305 showed a low to medium heritability (0.15 and 0.17, respectively). Conclusions. The model that best fit lactation curves in Holstein bovines is the Wood model. The average heritability and high genetic correlation between e y max and P305 indicate that it is possible to include them in breeding programs.
Sujets)
Lactation , Modèles génétiquesRésumé
We used the teratogen 5-hromodeoxy- uridine(BRDU)in the creation of a model of inherited congenital cataract in Wistar rats.The highest rate of impregnation(81%) of the rats was observed during the period oestrus.The frequency of occurrence and the density of the congenital cataract in the F1 generation varied with the dosage of BRDU,and the frequency of the cataract in the F2 generation was positively correla- ted with the dosage of the drug.The crea- tion of this inherited congenital cataract model may be useful in exploring the etio- logy of the cataract and its prevention and treatment.