PMID- 26232762
OWN - NLM
STAT- MEDLINE
DCOM- 20160226
LR  - 20220414
IS  - 1460-2105 (Electronic)
IS  - 0027-8874 (Linking)
VI  - 107
IP  - 10
DP  - 2015 Oct
TI  - The Imperative for a New Approach to Toxicity Analysis in Oncology Clinical 
      Trials.
LID - djv216 [pii]
LID - 10.1093/jnci/djv216 [doi]
AB  - A consistent system for reporting adverse events (AEs) is paramount in cancer 
      clinical trials and is crucial to ensure the safety and tolerability of 
      chemotherapy. The shift towards individualized medicine in oncology over the last 
      decade has brought with it an impressive array of novel, targeted therapies and 
      increasingly complex clinical trials to investigate them. Many of the newer drugs 
      are oral agents that are taken continuously over protracted periods of time. They 
      stand sharply in contrast to conventional cytotoxic intravenous chemotherapy 
      given over a prefixed number of cycles. With its narrow emphasis on high-grade 
      events, the consensus method for reporting of AEs in current cancer trials has 
      not evolved to reflect the longitudinal toxicity profiles of the newer agents. 
      Current methods do not incorporate patient-reported outcomes, which are of rising 
      importance when therapy lasts for months or even years in a patient's life. 
      Additionally, tables focusing on worst-grade events do not depict evolution of 
      toxicity over time and therefore cannot offer patients and clinicians information 
      about the onset or duration of a given AE. Most importantly, current methods do 
      not capture lower-grade but longer-lasting toxicity that may have important 
      ramifications on patients' quality of life. The failure to include any 
      time-related information in our current methods of toxicity reporting provides an 
      incomplete and even inaccurate depiction of AEs. To remain in step with the 
      advancing science of cancer and the vast array of new therapies with extended 
      treatment durations, our consensus method of AE analysis in oncology clinical 
      trials must modernize to include the dimension of time.
CI  - (c) The Author 2015. Published by Oxford University Press. All rights reserved. For 
      Permissions, please e-mail: journals.permissions@oup.com.
FAU - Thanarajasingam, Gita
AU  - Thanarajasingam G
AD  - Department of Medical Oncology (GT, JH, AG) and Alliance Statistics and Data 
      Center (JAS), Mayo Clinic, Rochester, MN. thanarajasingam.gita@mayo.edu.
FAU - Hubbard, Joleen M
AU  - Hubbard JM
AD  - Department of Medical Oncology (GT, JH, AG) and Alliance Statistics and Data 
      Center (JAS), Mayo Clinic, Rochester, MN.
FAU - Sloan, Jeff A
AU  - Sloan JA
AD  - Department of Medical Oncology (GT, JH, AG) and Alliance Statistics and Data 
      Center (JAS), Mayo Clinic, Rochester, MN.
FAU - Grothey, Axel
AU  - Grothey A
AD  - Department of Medical Oncology (GT, JH, AG) and Alliance Statistics and Data 
      Center (JAS), Mayo Clinic, Rochester, MN.
LA  - eng
PT  - Journal Article
DEP - 20150801
PL  - United States
TA  - J Natl Cancer Inst
JT  - Journal of the National Cancer Institute
JID - 7503089
RN  - 0 (Antineoplastic Agents)
SB  - IM
MH  - *Adverse Drug Reaction Reporting Systems/trends
MH  - Antineoplastic Agents/administration & dosage/*adverse effects
MH  - Clinical Trials as Topic
MH  - Humans
MH  - Neoplasms/*drug therapy
MH  - Quality of Life
MH  - *Severity of Illness Index
MH  - Time Factors
EDAT- 2015/08/02 06:00
MHDA- 2016/02/27 06:00
CRDT- 2015/08/02 06:00
PHST- 2014/12/01 00:00 [received]
PHST- 2015/07/09 00:00 [accepted]
PHST- 2015/08/02 06:00 [entrez]
PHST- 2015/08/02 06:00 [pubmed]
PHST- 2016/02/27 06:00 [medline]
AID - djv216 [pii]
AID - 10.1093/jnci/djv216 [doi]
PST - epublish
SO  - J Natl Cancer Inst. 2015 Aug 1;107(10):djv216. doi: 10.1093/jnci/djv216. Print 
      2015 Oct.