Paul Wants Terminally Ill Patients to Have Access to Experimental Drugs;Patients Cannot Sue If They Have Adverse Effect

2012 ◽  
Vol 31 (5) ◽  
pp. 466-466
Author(s):  
Rebecca Dresser

This chapter addresses access to unapproved drugs. Some terminally ill patients enroll in research as a way to gain access to experimental drugs. Other patients want to try the drugs without enrolling in research. The US Food and Drug Administration permits patients to do so under certain circumstances, but critics say the government rules are too restrictive. “Right to try” advocates campaign for laws permitting more liberal access, telling heart-wrenching stories about patients desperate to obtain experimental drugs. But the picture they present is one-sided. It disregards the negative impact that more liberal access policies may have on the drug trials that benefit society at large, and it ignores stories conveying the harm that can come from access to experimental drugs. These factors belong in the debate too.


JAMA ◽  
2008 ◽  
Vol 300 (23) ◽  
pp. 2793 ◽  
Author(s):  
Benjamin P. Falit

1986 ◽  
Author(s):  
J. H. Brown ◽  
P. Henteleff ◽  
S. Barakat ◽  
C. J. Rowe

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nanako Koyama ◽  
Chikako Matsumura ◽  
Yoshihiro Shitashimizu ◽  
Morito Sako ◽  
Hideo Kurosawa ◽  
...  

Abstract Background The clinical use of patient-reported outcomes as compared to inflammatory biomarkers for predicting cancer survival remains a challenge in palliative care settings. We evaluated the role of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative scores (EORTC QLQ-C15-PAL) and the inflammatory biomarkers C-reactive protein (CRP), albumin (Alb), and neutrophil-lymphocyte ratio (NLR) for survival prediction in patients with advanced cancer. Methods This was an observational study in terminally ill patients with cancer hospitalized in a palliative care unit between June 2018 and December 2019. Patients’ data collected at the time of hospitalization were analyzed. Cox regression was performed to examine significant factors influencing survival. A receiver operating characteristic (ROC) analysis was performed to estimate cut-off values for predicting survival within 3 weeks, and a log-rank test was performed to compare survival curves between groups divided by the cut-off values. Results Totally, 130 patients participated in the study. Cox regression suggested that the QLQ-C15-PAL dyspnea and fatigue scores and levels of CRP, Alb, and NLR were significantly associated with survival time, and cut-off values were 66.67, 66.67, 3.0 mg/dL, 2.5 g/dL, and 8.2, respectively. The areas under ROC curves of these variables were 0.6–0.7. There were statistically significant differences in the survival curves between groups categorized using each of these cut-off values (p < .05 for all cases). Conclusion Our findings suggest that the assessment of not only objective indicators for the systemic inflammatory response but also patient-reported outcomes using EORTC QLQ-C15-PAL is beneficial for the prediction of short-term survival in terminally ill patients with cancer.


Author(s):  
Nanako Koyama ◽  
Chikako Matsumura ◽  
Yuuna Tahara ◽  
Morito Sako ◽  
Hideo Kurosawa ◽  
...  

Abstract Purpose The aims of the present study were to investigate the symptom clusters in terminally ill patients with cancer using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative Care (EORTC QLQ-C15-PAL), and to examine whether these symptom clusters influenced prognosis. Methods We analyzed data from 130 cancer patients hospitalized in the palliative care unit from June 2018 to December 2019 in an observational study. Principal component analysis was used to detect symptom clusters using the scored date of 14 items in the QLQ-C15-PAL, except for overall QOL, at the time of hospitalization. The influence of the existence of these symptom clusters and Palliative Performance Scale (PPS) on survival was analyzed by Cox proportional hazards regression analysis, and survival curves were compared between the groups with or without existing corresponding symptom clusters using the log-rank test. Results The following symptom clusters were identified: cluster 1 (pain, insomnia, emotional functioning), cluster 2 (dyspnea, appetite loss, fatigue, and nausea), and cluster 3 (physical functioning). Cronbach’s alpha values for the symptom clusters ranged from 0.72 to 0.82. An increased risk of death was significantly associated with the existence of cluster 2 and poor PPS (log-rank test, p = 0.016 and p < 0.001, respectively). Conclusion In terminally ill patients with cancer, three symptom clusters were detected based on QLQ-C15-PAL scores. Poor PPS and the presence of symptom cluster that includes dyspnea, appetite loss, fatigue, and nausea indicated poor prognosis.


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