Background: The purpose of this study is to investigate the prognostic factors of stereotactic radiotherapy for stage I NSCLC to improve outcomes.

Methods: Stage I non-small cell lung cancer patients who were treated with stereotactic radiotherapy between 2005 and 2009 at our hospital were enrolled in this study. The primary endpoint was local control rate. Survival estimates were calculated from the completion date of radiotherapy using the Kaplan-Meier method. The prognostic factors including patients' characteristics and dose-volume histogram parameters were evaluated using Cox's proportional hazard regression model.

Results: Eighty patients (81 lesions) treated with 3 dose levels, 48 Gy/4 fractions, 60 Gy/8 fractions and 60 Gy/15 fractions, were enrolled in this study. Median follow-up was 30.4 months (range, 0.3 - 78.5 months). A Cox regression model showed T factor (p = 0.013), biological effective dose calculated from prescribed dose (BED10) (p = 0.048), and minimum dose for PTV (p = 0.013) to be prognostic factors for local control. Three-year overall survival rate and local control rate were 89.9% (T1: 86.8%, T2: 100%) and 89.0% (T1: 97.9%; T2: 64.8%), respectively. When the 3-year local control rates were examined by prescribed doses, they were 100% for the dose per fraction of 48 Gy /4 fractions (105.6 Gy BED10), 82.1% for 60 Gy/8 fractions (105 Gy BED10), and 57.1% for 60 Gy/15 fractions (84 Gy BED10). The median value of the minimum dose for PTV (%) was 89.88 (%), and the 3-year local control rates were 100% in those with the minimum dose for PTV (%) ≥ 89.88% and 79.2% in those with the minimum dose for PTV (%) < 89.88%.

Conclusions: Our results suggest that T factor, BED10, and minimum dose for PTV influence the local control rate. Local control rate can be improved by securing the minimum dose for PTV.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3542195PMC
http://dx.doi.org/10.1186/1748-717X-7-182DOI Listing

Publication Analysis

Top Keywords

local control
32
minimum dose
24
dose ptv
24
prognostic factors
16
control rate
16
stereotactic radiotherapy
12
dose
10
local
8
factors local
8
control
8

Similar Publications

Hepatitis C virus (HCV) infection is a significant risk factor for liver cirrhosis and hepatocellular carcinoma (HCC). Traditionally, the primary prevention strategy for HCV-associated HCC has focused on removing infection through antiviral regimes. Currently, highly effective direct-acting antivirals (DAAs) offer extraordinary success across all patient categories, including cirrhotics.

View Article and Find Full Text PDF

Background: Point-of-care hepatitis C virus (HCV) testing streamlines testing and treatment pathways. In this study, we established an HCV model of care in a homelessness service by offering antibody and RNA point-of-care testing.

Methods: A nurse and peer-led HCV model of care with peer support were implemented between November 2021 and April 2022 at a homelessness service in Adelaide, Australia.

View Article and Find Full Text PDF

Detection of Hepatitis C Virus Infection from Patient Sera in Cell Culture Using Semi-Automated Image Analysis.

Viruses

November 2024

Department of Infectious Diseases, Molecular Virology, Section Virus-Host Interactions, Heidelberg University, 69120 Heidelberg, Germany.

The study of hepatitis C virus (HCV) replication in cell culture is mainly based on cloned viral isolates requiring adaptation for efficient replication in Huh7 hepatoma cells. The analysis of wild-type (WT) isolates was enabled by the expression of SEC14L2 and by inhibitors targeting deleterious host factors. Here, we aimed to optimize cell culture models to allow infection with HCV from patient sera.

View Article and Find Full Text PDF

In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.

View Article and Find Full Text PDF

: Yellow fever (YF) outbreaks continue to affect populations that are not reached by routine immunization services, such as workers at a high risk of occupational exposure to YF. In the Central African Republic (CAR), YF cases were detected in districts characterized by the presence of workers in forest areas. We developed an innovative approach based on a local partnership with private companies of the extractive industry to administer YF vaccine to workers in remote areas during the response to an outbreak.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!