Changes in survival of patients with non-small cell lung cancer in Japan: An interrupted time series study

Yukari Taniyama1, Isao Oze2, Yuriko N Koyanagi1

  • 1Division of Cancer Information and Control, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan.

Cancer Science
|November 12, 2022
PubMed

Insights

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) improved survival for non-small cell lung cancer (NSCLC) patients in Japan. Introduction of EGFR-TKIs and mutation testing correlated with better real-world outcomes, especially for adenocarcinoma.

Area of Science:

  • Oncology
  • Public Health
  • Pharmacoeconomics

Background:

  • Gefitinib and erlotinib (EGFR-TKIs) were approved for metastatic or relapsed non-small cell lung cancer (NSCLC) in Japan in 2002 and 2007.
  • EGFR mutation testing approval in 2007 aimed to guide treatment selection.
  • Real-world effectiveness of EGFR-TKIs in NSCLC patients with EGFR mutations remained under-reported.

Purpose of the Study:

  • To evaluate survival changes in NSCLC patients following the introduction of EGFR-TKIs and EGFR mutation testing in Japan.
  • To assess the real-world impact of these targeted therapies and diagnostic tools on patient survival.
  • To analyze survival trends across different patient demographics and disease stages.

Main Methods:

  • Utilized data from six prefectural population-based cancer registries in Japan, covering NSCLC patients diagnosed between 1993 and 2011.
  • Calculated relative survival (RS) rates stratified by sex, histological subtype, and cancer stage.
  • Employed interrupted time series analysis to detect survival changes post-introduction of EGFR-TKIs and mutation testing.

Main Results:

  • Analyzed 120,068 NSCLC patients, observing gradual increases in 1- and 3-year RS for both men and women.
  • Identified steep increases in 1- and 3-year RS for male adenocarcinoma patients diagnosed from 2007-2011.
  • Observed significant level increases in 1-year RS for female adenocarcinoma patients, particularly those with advanced-stage disease, following drug and testing introductions.

Conclusions:

  • Recent survival improvements in Japanese NSCLC patients, especially with adenocarcinoma, are partly attributed to the real-world implementation of EGFR-TKIs.
  • Appropriate patient selection through EGFR mutation testing has likely enhanced the effectiveness of these targeted therapies in clinical practice.
  • The study highlights the positive impact of targeted therapy introduction and companion diagnostics on population-level cancer survival outcomes.

Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
418
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
248
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
226
Treatment Resistant Cancers02:56

Treatment Resistant Cancers

Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
3.4K
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
174
Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
112