An (18)F-FDG PET/CT and mean lung dose model to predict early radiation pneumonitis in stage III non-small cell lung cancer patients treated with chemoradiation and immunotherapy Journal Article


Authors: Thor, M.; Lee, C.; Sun, L.; Patel, P.; Apte, A.; Grkovski, M.; Shepherd, A. F.; Gelblum, D. Y.; Wu, A. J.; Simone, C. B. 2nd; Chaft, J. E.; Rimner, A.; Gomez, D. R.; Deasy, J. O.; Shaverdian, N.
Article Title: An (18)F-FDG PET/CT and mean lung dose model to predict early radiation pneumonitis in stage III non-small cell lung cancer patients treated with chemoradiation and immunotherapy
Abstract: Radiation pneumonitis (RP) that develops early (i.e., within 3mo) (RPEarly) after completion of concurrent chemoradiation (cCRT) leads to treatment discontinuation and poorer survival for patients with stage III non-small cell lung cancer. Since no RPEarly risk model exists, we explored whether published RP models and pretreatment 18FFDG PET/CT-derived features predict RPEarly. Methods: One hundred sixty patients with stage III non-small cell lung cancer treated with cCRT and consolidative immunotherapy were analyzed for RPEarly. Three published RP models that included the mean lung dose (MLD) and patient characteristics were examined. Pretreatment 18F-FDG PET/CT normal-lung SUV featured included the following: 10th percentile of SUV (SUVP10), 90th percentile of SUV (SUVP90), SUVmax, SUVmean, minimum SUV, and SD. Associations between models/ features and RPEarly were assessed using area under the receiveroperating characteristic curve (AUC), P values, and the Hosmer- Lemeshow test (pHL). The cohort was randomly split, with similar RPEarly rates, into a 70%/30% derivation/internal validation subset. Results: Twenty (13%) patients developed RPEarly. Predictors for RPEarly were MLD alone (AUC, 0.72; P = 0.02; pHL, 0.87), SUVP10, SUVP90, and SUVmean (AUC, 0.70-0.74; P = 0.003-0.006; pHL, 0.67- 0.70). The combined MLD and SUVP90 model generalized in the validation subset and was deemed the final RPEarly model (RPEarly risk 5 1/[11e(2x)]; x5 26.08 1 [0.17 3 MLD] 1 [1.63 3 SUVP90]). The final model refitted in the 160 patients indicated improvement over the published MLD-alone model (AUC, 0.77 vs. 0.72; P = 0.0001 vs. 0.02; pHL, 0.65 vs. 0.87). Conclusion: Patients at risk for RPEarly can be detected with high certainty by combining the normal lung's MLD and pretreatment 18F-FDG PET/CT SUVP90. This refined model can be used to identify patients at an elevated risk for premature immunotherapy discontinuation due to RPEarly and could allow for interventions to improve treatment outcomes. © 2024 by the Society of Nuclear Medicine andMolecular Imaging.
Keywords: adult; controlled study; aged; retrospective studies; unclassified drug; major clinical study; area under the curve; treatment planning; validation process; cancer radiotherapy; radiation dose; cancer staging; antineoplastic agent; cancer immunotherapy; radiation; carcinoma, non-small-cell lung; lung neoplasms; cohort analysis; diagnostic imaging; radiation injury; retrospective study; prediction; risk; lung tumor; statistical significance; immunotherapy; fluorodeoxyglucose f 18; fluorodeoxyglucose f18; lung; non-small cell lung cancer; radiation pneumonia; chemoradiotherapy; pet/ct; clinical assessment tool; pneumonitis; non small cell lung cancer; concurrent chemoradiation; clinical outcome; radiation pneumonitis; oncological parameters; very elderly; humans; human; male; female; article; internal validation; durvalumab; mean lung dose; positron emission tomography-computed tomography; positron emission tomography computed tomography; cisplatin plus etoposide; carboplatin plus paclitaxel; carboplatin plus pemetrexed; cisplatin plus pemetrexed; hosmer lemeshow test; standardized uptake value ratio
Journal Title: Journal of Nuclear Medicine
Volume: 65
Issue: 4
ISSN: 0161-5505
Publisher: Society of Nuclear Medicine  
Date Published: 2024-04-01
Start Page: 520
End Page: 526
Language: English
DOI: 10.2967/jnumed.123.266965
PUBMED: 38485270
PROVIDER: scopus
PMCID: PMC10995528
DOI/URL:
Notes: Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PDF -- MSK corresponding author is Maria Thor -- Source: Scopus
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MSK Authors
  1. Daphna Y Gelblum
    228 Gelblum
  2. Daniel R Gomez
    242 Gomez
  3. Jamie Erin Chaft
    290 Chaft
  4. Andreas Rimner
    527 Rimner
  5. Abraham Jing-Ching Wu
    404 Wu
  6. Joseph Owen Deasy
    527 Deasy
  7. Aditya Apte
    205 Apte
  8. Maria Elisabeth Thor
    150 Thor
  9. Annemarie Fernandes Shepherd
    103 Shepherd
  10. Charles Brian Simone
    194 Simone
  11. Lian Sun
    3 Sun
  12. Purvi S Patel
    4 Patel
  13. Chen Chiao Lee
    5 Lee