Patients with lung cancer may experience various symptoms as the disease progresses,which may reduce the benefits of cancer treatment,reduce treatment compliance,delay cancer treatment,reduce the quality of life(QoL),...Patients with lung cancer may experience various symptoms as the disease progresses,which may reduce the benefits of cancer treatment,reduce treatment compliance,delay cancer treatment,reduce the quality of life(QoL),and impact survival.This review discusses comprehensive symptom assessment and management,which are crucial for high-quality lung cancer treatment.Traditional Chinese medicine(TCM)is important in relieving cancer-related symptoms in patients with lung cancer.Including patient-reported outcomes(PROs)in clinical trials and practice can provide a better assessment of symptom burden and the effectiveness of symptom management.Patient-centered care with TCM in lung cancer patients may include six steps:Symptom screening,etiology investigation,comprehensive assessment,integrative management,reassessment,and regular symptom follow-up monitoring.PRO measures can be used to evaluate symptom intensity,the degree to which symptoms interfere with activities of daily living,and the QoL.Clearly defined and reliable PRO measures can enhance patient satisfaction and improve symptom control.Quantitative PRO measures developed from the TCM perspective should be considered one of the important outcome measurements in TCM care.A multidisciplinary collaborative symptom management model,including TCM and conventional therapy,will be the future goal for treating patients with lung cancer.展开更多
The lasso of Tibshirani （1996） is a least-squares problem regularized by the l1 norm. Due to the sparseness promoting property of the l1 norm, the lasso has been received much attention in recent years. In this pape...The lasso of Tibshirani （1996） is a least-squares problem regularized by the l1 norm. Due to the sparseness promoting property of the l1 norm, the lasso has been received much attention in recent years. In this paper some basic properties of the lasso and two variants of it are exploited. Moreover, the proximal method and its variants such as the relaxed proximal algorithm and a dual method for solving the lasso by iterative algorithms are presented.展开更多
基金financially supported by the Capital Clinical Characteristic Application Research Project of the Beijing Science and Technology Commission(No.Z181100001718175)the Scientific and Technological Innovation Project of the China Academy of Chinese Medical Sciences(No.CI2021A05502)。
文摘Patients with lung cancer may experience various symptoms as the disease progresses,which may reduce the benefits of cancer treatment,reduce treatment compliance,delay cancer treatment,reduce the quality of life(QoL),and impact survival.This review discusses comprehensive symptom assessment and management,which are crucial for high-quality lung cancer treatment.Traditional Chinese medicine(TCM)is important in relieving cancer-related symptoms in patients with lung cancer.Including patient-reported outcomes(PROs)in clinical trials and practice can provide a better assessment of symptom burden and the effectiveness of symptom management.Patient-centered care with TCM in lung cancer patients may include six steps:Symptom screening,etiology investigation,comprehensive assessment,integrative management,reassessment,and regular symptom follow-up monitoring.PRO measures can be used to evaluate symptom intensity,the degree to which symptoms interfere with activities of daily living,and the QoL.Clearly defined and reliable PRO measures can enhance patient satisfaction and improve symptom control.Quantitative PRO measures developed from the TCM perspective should be considered one of the important outcome measurements in TCM care.A multidisciplinary collaborative symptom management model,including TCM and conventional therapy,will be the future goal for treating patients with lung cancer.
文摘The lasso of Tibshirani （1996） is a least-squares problem regularized by the l1 norm. Due to the sparseness promoting property of the l1 norm, the lasso has been received much attention in recent years. In this paper some basic properties of the lasso and two variants of it are exploited. Moreover, the proximal method and its variants such as the relaxed proximal algorithm and a dual method for solving the lasso by iterative algorithms are presented.
