Understanding Tumor Growth in Lung Cancer Immunotherapy
Author Information
Author(s): Felfli Mehdi, Thinnes Alexandre, Jacques Sebastien, Liu Yan, Iannessi Antoine
Primary Institution: Median Technologies, Imaging Lab, Valbonne, France
Hypothesis
Can early tumor growth dynamics predict clinical outcomes in non-small cell lung cancer patients receiving immunotherapy?
Conclusion
The study found that early tumor growth parameters can help predict long-term outcomes and treatment responses in lung cancer patients undergoing immunotherapy.
Supporting Evidence
- Lower growth rate and model parameter M were associated with longer progression-free survival.
- Higher growth rate and parameter A correlated with shorter time to response.
- Responders had significantly lower A and higher growth rates than non-responders.
Takeaway
This study shows that by looking at how tumors grow early on during treatment, doctors can better understand how well the treatment is working for lung cancer patients.
Methodology
The study analyzed data from 861 patients using a novel Gompertz model to assess tumor growth dynamics and their correlation with clinical outcomes.
Potential Biases
Potential bias due to exclusion of patients with limited therapy response and lack of treatment arm indication.
Limitations
The study lacked overall survival data and had a small number of patients with pseudo-progression and hyper-progression patterns.
Participant Demographics
Patients with non-small cell lung cancer at stages IIIB and IV, aged 18 and older.
Statistical Information
P-Value
p=1.51e-53
Confidence Interval
95% CI: 0.489 - 0.677
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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