Back

Mathematical analysis of the overall survival after chemoradiotherapy of limited-stage small cell lung cancer and the effect of dose/fractionation

Bunuel-Muriscot, A.; Gonzalez-Crespo, I.; Otero-Casal, P.; Gomez-Caamano, A.; Pardo-Montero, J.

2026-06-12 oncology
10.64898/2026.06.11.26355440 medRxiv
Show abstract

The purpose of this work is to analyze the 2-year overall survival (OS2y) of limited-stage small cell lung cancer (LS-SCLC) treated with chemoradiotherapy (CRT), aiming at characterizing the response of LS-SCLC, and in particular the /{beta} value and proliferation parameters. Through a systematic analysis of the literature, we collated a dataset containing 57 entries (3363 patients) of response of LS-SCLC treated with CRT. Radiotherapy schedules ranged from hyper- to hypofractionation. Four radiobiological models to describe the OS2y were investigated, with progressive levels of complexity including the effect of radiotherapy, chemotherapy, treatment year and toxicity. The Akaike Information Criterion (AIC) was used to compare models, and the profile likelihood methodology to compute confidence intervals. Model 4, which includes the effect of radiotherapy, chemotherapy, treatment year and dose-dependent toxicity, provided the best fits of the experimental data (lowest AIC value). While being the best model, model 4 still fails to provide a good prediction of the OS2y, in particular failing to predict the survival of the schedules achieving the lower/higher survivals. The radiobiological analysis of the dose-response of LS-SCLC to CRT does not allow to narrowly constrain the value of response parameters. We attribute this limitation to the large heterogeneity of this disease. Nonetheless, our analysis shows a large /{beta} value (>9 Gy, 95% CI), which implies a low fractionation effect in the radiotherapy of LS-SCLC. and an accelerated proliferation of tumor cells, {lambda}' > 1.6 Gy/day (95% CI), after a kick-off time of ~4-5 weeks, which supports the use of accelerated protocols to avoid the effect of tumor proliferation on the clinical outcome.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Radiotherapy and Oncology
18 papers in training set
Top 0.1%
22.4%
2
Cancers
200 papers in training set
Top 0.2%
14.3%
3
International Journal of Radiation Oncology*Biology*Physics
21 papers in training set
Top 0.1%
12.6%
4
Scientific Reports
3102 papers in training set
Top 10%
8.4%
50% of probability mass above
5
Frontiers in Oncology
95 papers in training set
Top 0.7%
4.8%
6
PLOS ONE
4510 papers in training set
Top 31%
4.8%
7
Computers in Biology and Medicine
120 papers in training set
Top 0.9%
3.6%
8
Medical Physics
14 papers in training set
Top 0.3%
2.1%
9
PLOS Computational Biology
1633 papers in training set
Top 15%
1.9%
10
British Journal of Cancer
42 papers in training set
Top 0.9%
1.7%
11
BMC Cancer
52 papers in training set
Top 2%
1.3%
12
JNCI: Journal of the National Cancer Institute
16 papers in training set
Top 0.6%
0.9%
13
Aging
69 papers in training set
Top 2%
0.9%
14
Journal of Clinical Medicine
91 papers in training set
Top 6%
0.8%
15
Annals of Oncology
13 papers in training set
Top 0.9%
0.8%
16
European Journal of Cancer
10 papers in training set
Top 0.5%
0.7%
17
JCO Precision Oncology
14 papers in training set
Top 0.4%
0.7%
18
Journal of Translational Medicine
46 papers in training set
Top 3%
0.7%
19
Cancer Letters
32 papers in training set
Top 0.9%
0.7%
20
International Journal of Molecular Sciences
453 papers in training set
Top 16%
0.7%
21
Computer Methods and Programs in Biomedicine
27 papers in training set
Top 1%
0.7%
22
PeerJ
261 papers in training set
Top 16%
0.7%
23
Biochemistry and Biophysics Reports
28 papers in training set
Top 2%
0.6%
24
Interface Focus
14 papers in training set
Top 0.4%
0.6%
25
Cancer Medicine
24 papers in training set
Top 2%
0.6%
26
Annals of Biomedical Engineering
34 papers in training set
Top 1%
0.6%
27
Cancer Research Communications
46 papers in training set
Top 2%
0.6%