A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer

2016 ◽  
Vol 100 (6) ◽  
pp. 672-684 ◽  
Author(s):  
GK Raju ◽  
K Gurumurthi ◽  
R Domike ◽  
D Kazandjian ◽  
G Blumenthal ◽  
...  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. Or ◽  
B. Liu ◽  
J. Lam ◽  
S. Vinod ◽  
W. Xuan ◽  
...  

AbstractTreatment-related toxicity is an important component in non-small cell lung cancer (NSCLC) management decision-making. Our aim was to evaluate and compare the toxicity rates of curative and palliative radiotherapy with and without chemotherapy. This meta-analysis provides better quantitative estimates of the toxicities compared to individual trials. A systematic review of randomised trials with > 50 unresectable NSCLC patients, treated with curative or palliative conventional radiotherapy (RT) with or without chemotherapy. Data was extracted for oesophagitis, pneumonitis, cardiac events, pulmonary fibrosis, myelopathy and neutropenia by any grade, grade ≥ 3 and treatment-related deaths. Mantel–Haenszel fixed-effect method was used to obtain pooled risk ratio. Forty-nine trials with 8609 evaluable patients were included. There was significantly less grade ≥ 3 acute oesophagitis (6.4 vs 22.2%, p < 0.0001) and any grade oesophagitis (70.4 vs 79.0%, p = 0.04) for sequential CRT compared to concurrent CRT, with no difference in pneumonitis (grade ≥ 3 or any grade), neutropenia (grade ≥ 3), cardiac events (grade ≥ 3) or treatment-related deaths. Although the rate of toxicity increased with intensification of treatment with RT, the only significant difference between treatment regimens was the rate of oesophagitis between the use of concurrent and sequential CRT. This can aid clinicians in radiotherapy decision making for NSCLC.


2020 ◽  
Vol 149 ◽  
pp. 84-88 ◽  
Author(s):  
P.M. Putora ◽  
G.F. Fischer ◽  
M. Früh ◽  
R. Califano ◽  
C. Faivre-Finn ◽  
...  

2014 ◽  
Vol 97 (6) ◽  
pp. 1920-1925 ◽  
Author(s):  
Hyun Jin Cho ◽  
Sung Ryong Kim ◽  
Hyeong Ryul Kim ◽  
Jin-Ok Han ◽  
Yong-Hee Kim ◽  
...  

Author(s):  
Cecilia Pompili ◽  
Sanjush Dalmia ◽  
Finn McLennan Battleday ◽  
Zoe Rogers ◽  
Kate Absolom ◽  
...  

Abstract Purpose Patient-reported outcome measures, including satisfaction with treatment decisions, provide important information in addition to clinical outcomes, survival and decision-making in lung cancer surgery. We investigated associations between preoperative clinical and socio-demographic factors and patient-reported satisfaction 6 weeks after radical treatment for early-stage non-small cell lung cancer (NSCLC). Methods We conducted a sub-group analysis of the prospective observational longitudinal study of 225 participants in two treatment groups—surgical (VATS) and radiotherapy (SABR). The Patient Satisfaction Questionnaire-18 (PSQ-18) was used to measure patient satisfaction 6 weeks after treatment. Clinical variables, Index of Multiple Deprivation decile and Decision self-efficacy scores were used in regression analysis. Variables with a p level < 0.1 were used as independent predictors in generalised linear logistic regression analyses. Results As expected, the two groups differed in pre-treatment clinical features. The SABR group experienced more grade 1–2 complications than the VATS group. No differences were found between the groups in any subscale of the PSQ-18 questionnaire. Patients experiencing complications or living in more deprived areas were more satisfied with care. Properative factors independently associated with patient satisfaction were the efficacy in decision-making and age. Conclusion We showed that efficacy in treatment decision-making and age was the sole predictor of patient satisfaction with their care after radical treatment for early-stage NSCLC. Patients from more deprived areas and patients who suffered complications reported greater subsequent satisfaction. Involving patients in their care may improve satisfaction after treatment for early-stage NSCLC.


2019 ◽  
Vol 30 ◽  
pp. ii22 ◽  
Author(s):  
J. Liu ◽  
H. Zhou ◽  
Y. Zhang ◽  
W. Fang ◽  
Y. Yang ◽  
...  

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