PMID- 37545289
OWN - NLM
STAT- MEDLINE
DCOM- 20240325
LR  - 20240325
IS  - 1423-0380 (Electronic)
IS  - 1010-4283 (Linking)
VI  - 46
IP  - s1
DP  - 2024
TI  - Comparing modeling strategies combining changes in multiple serum tumor 
      biomarkers for early prediction of immunotherapy non-response in non-small cell 
      lung cancer.
PG  - S269-S281
LID - 10.3233/TUB-220022 [doi]
AB  - BACKGROUND: Patients treated with immune checkpoint inhibitors (ICI) are at risk 
      of adverse events (AEs) even though not all patients will benefit. Serum tumor 
      markers (STMs) are known to reflect tumor activity and might therefore be useful 
      to predict response, guide treatment decisions and thereby prevent AEs. 
      OBJECTIVE: This study aims to compare a range of prediction methods to predict 
      non-response using multiple sequentially measured STMs. METHODS: Nine prediction 
      models were compared to predict treatment non-response at 6-months (n = 412) 
      using bi-weekly CYFRA, CEA, CA-125, NSE, and SCC measurements determined in the 
      first 6-weeks of therapy. All methods were applied to six different biomarker 
      combinations including two to five STMs. Model performance was assessed based on 
      sensitivity, while model training aimed at 95% specificity to ensure a low 
      false-positive rate. RESULTS: In the validation cohort, boosting provided the 
      highest sensitivity at a fixed specificity across most STM combinations (12.9% 
      -59.4%). Boosting applied to CYFRA and CEA achieved the highest sensitivity on 
      the validation data while maintaining a specificity >95%. CONCLUSIONS: 
      Non-response in NSCLC patients treated with ICIs can be predicted with a 
      specificity >95% by combining multiple sequentially measured STMs in a prediction 
      model. Clinical use is subject to further external validation.
FAU - van Delft, Frederik A
AU  - van Delft FA
AD  - Health Technology and Services Research Department, Technical Medical Centre, 
      University of Twente, Enschede, The Netherlands.
FAU - Schuurbiers, Milou M F
AU  - Schuurbiers MMF
AD  - Department of Respiratory Diseases, Radboud University Medical Center, Nijmegen, 
      the Netherlands.
FAU - Muller, Mirte
AU  - Muller M
AD  - Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, The 
      Netherlands.
FAU - Burgers, Sjaak A
AU  - Burgers SA
AD  - Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, The 
      Netherlands.
FAU - van Rossum, Huub H
AU  - van Rossum HH
AD  - Department of Laboratory Medicine, Netherlands Cancer Institute, Amsterdam, The 
      Netherlands.
FAU - IJzerman, Maarten J
AU  - IJzerman MJ
AD  - Health Technology and Services Research Department, Technical Medical Centre, 
      University of Twente, Enschede, The Netherlands.
AD  - Erasmus School of Health Policy and Management, Rotterdam, The Netherlands.
AD  - Centre for Cancer Research and Centre for Health Policy, University of Melbourne, 
      Parkville, Melbourne, Australia.
AD  - Peter MacCallum Cancer Centre, Parkville, Melbourne, Australia.
FAU - van den Heuvel, Michel M
AU  - van den Heuvel MM
AD  - Department of Respiratory Diseases, Radboud University Medical Center, Nijmegen, 
      the Netherlands.
FAU - Koffijberg, Hendrik
AU  - Koffijberg H
AD  - Health Technology and Services Research Department, Technical Medical Centre, 
      University of Twente, Enschede, The Netherlands.
LA  - eng
PT  - Journal Article
PL  - Netherlands
TA  - Tumour Biol
JT  - Tumour biology : the journal of the International Society for Oncodevelopmental 
      Biology and Medicine
JID - 8409922
RN  - 0 (Biomarkers, Tumor)
SB  - IM
MH  - Humans
MH  - *Carcinoma, Non-Small-Cell Lung/pathology
MH  - Biomarkers, Tumor
MH  - *Lung Neoplasms/pathology
MH  - Immunotherapy
OTO - NOTNLM
OT  - NSCLC
OT  - artificial intelligence
OT  - biomarkers
OT  - immunotherapy
OT  - machine learning
OT  - response prediction
OT  - serum tumor markers
EDAT- 2023/08/07 06:42
MHDA- 2024/03/25 06:43
CRDT- 2023/08/07 03:10
PHST- 2024/03/25 06:43 [medline]
PHST- 2023/08/07 06:42 [pubmed]
PHST- 2023/08/07 03:10 [entrez]
AID - TUB220022 [pii]
AID - 10.3233/TUB-220022 [doi]
PST - ppublish
SO  - Tumour Biol. 2024;46(s1):S269-S281. doi: 10.3233/TUB-220022.