Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors?
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Patients
2.2. Imaging
2.3. Model Development
2.4. Validation
2.5. Statistical Analysis
3. Results
3.1. Patients’ Characteristics
3.2. Random Forest Models for Binarised Best Overall Therapy Response
3.3. Random Forest Models for Progression-Free Survival
3.4. Random Forest Models for Overall Survival
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
ALM | acral lentiginous melanoma |
AUC | area under the curve |
BRAF | v-Raf murine sarcoma viral oncogene homolog B1 |
CI | confidence interval |
CR | complete response |
CT | computed tomography |
CTLA-4 | cytotoxic T-lymphocyte-associated protein 4 |
CV | cross-validation |
IQR | interquartile range |
LDH | lactate dehydrogenase |
LMM | lentigo maligna melanoma |
n | number |
NM | nodular melanoma |
OS | overall survival |
PACS | picture archiving and communication system |
PD | progressive disease |
PD-1 | programmed death 1 |
PET | positron emission tomography |
PFS | progression-free survival |
PR | partial response |
RECIST | Response Evaluation Criteria In Solid Tumors |
ROC | receiver operating characteristic |
SD | stable disease |
SSM | superficial spreading melanoma |
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Clinical Data | ||
---|---|---|
Age (years) [median, (IQR)] | 66 (22%) | |
Gender (male) [n, %] | 92 (63%) | |
Localization of primary tumour [n, %] | head/neck | 34 (23%) |
torso | 35 (24%) | |
upper extremity | 21 (14%) | |
lower extremity | 38 (26%) | |
other | 7 (5%) | |
n/a | 11 (8%) | |
Histological subtype [n, %] | SSM | 35 (24%) |
NM | 41 (28%) | |
LMM | 8 (5%) | |
ALM | 22 (14%) | |
mucosal | 7 (5%) | |
occult | 9 (6%) | |
n/a | 27 (18%) | |
BRAF V600E mutation status [n, %] | BRAF wildtype | 101 (69%) |
BRAF mutation | 41 (28%) | |
n/a | 4 (3%) | |
Baseline LDH [n, %] | normal (<250 U/L) | 31 (21%) |
elevated (≥250 U/L) | 100 (69%) | |
n/a | 15 (10%) | |
FU1 LDH [n, %] | normal (<250 U/L) | 86 (59%) |
elevated (≥250 U/L) | 57 (39%) | |
n/a | 3 (2%) | |
Baseline S100B [n, %] | normal (<0.1 µg/L) | 77 (53%) |
elevated (≥0.1 µg/L) | 59 (40%) | |
n/a | 10 (7%) | |
FU1 S100B [n, %] | normal (<0.1 µg/L) | 80 (55%) |
elevated (≥0.1 µg/L) | 61 (42%) | |
n/a | 5 (3%) | |
Number of metastatic organs [n, %] | 1–3 | 132 (90%) |
> 3 | 14 (1%) | |
Presence of cerebral metastases [n, %] | 23 (16%) | |
Presence of hepatic metastases [n, %] | 39 (27%) | |
Therapy [n, %] | pembrolizumab | 61 (42%) |
nivolumab | 19 (13%) | |
nivolumab + ipilimumab | 66 (45%) | |
Baseline CT lesion counts [n] | all | 3188 |
lung | 1411 | |
liver | 584 | |
soft tissue/skin | 416 | |
lymph nodes | 478 | |
skeletal | 77 | |
spleen | 74 | |
other | 148 | |
FU1 CT lesion counts [n] | all | 4836 |
lung | 2104 | |
liver | 1083 | |
soft tissue/skin | 707 | |
lymph nodes | 588 | |
skeletal | 71 | |
spleen | 92 | |
other | 191 | |
Patient outcome | ||
Best overall response (RECIST 1.1) [n, %] | CR | 26 (18%) |
PR | 46 (31%) | |
SD | 22 (15%) | |
PD | 48 (33%) | |
n/a | 4 (3%) | |
Progression-free survival for 6 months [n, %] | yes | 68 (44%) |
no | 66 (48%) | |
n/a | 12 (8%) | |
Progression-free survival for 9 months [n, %] | yes | 54 (37%) |
no | 73 (50%) | |
n/a | 19 (13%) | |
Progression-free survival for 12 months [n, %] | yes | 41 (28%) |
no | 77 (53%) | |
n/a | 28 (19%) | |
Overall survival after 6 months [n, %] | yes | 110 (75%) |
no | 19 (13%) | |
n/a | 17 (12%) | |
Overall survival after 9 months [n, %] | yes | 90 (62%) |
no | 27 (18%) | |
n/a | 29 (20%) | |
Overall survival after 12 months [n, %] | yes | 70 (48%) |
no | 30 (21%) | |
n/a | 46 (31%) |
Binary Endpoint | Cases n (Class 0 + 1) | Model with Clinical Features Only. AUC (95%CI) | Model with Clinical Features + Whole- Tumour-Load Radiomic Features. AUC (95%CI) | Model with Clinical Features + Radiomic Features from Largest Ten Lesions. AUC (95%CI) |
---|---|---|---|---|
Best overall response | 142 (70 + 72) | 0.750 (0.672, 0.822) | 0.811 (0.745, 0.876) | 0.794 (0.726, 0.862) |
PFS 6 months | 134 (66 + 68) | 0.797 (0.726, 0.859) | 0.824 (0.756, 0.882) | 0.814 (0.747, 0.874) |
PFS 9 months | 127 (73 + 54) | 0.764 (0.684, 0.832) | 0.797 (0.730, 0.855) | 0.774 (0.702, 0.841) |
PFS 12 months | 118 (77 + 41) | 0.742 (0.658, 0.816) | 0.769 (0.698, 0.839) | 0.741 (0.667, 0.815) |
OS 6 months | 129 (19 + 110) | 0.721 (0.588, 0.848) | 0.742 (0.598, 0.870) | 0.718 (0.583, 0.852) |
OS 9 months | 117 (27 + 90) | 0.684 (0.568, 0.788) | 0.704 (0.594, 0.808) | 0.708 (0.590, 0.811) |
OS 12 months | 101 (31 + 70) | 0.724 (0.617, 0.822) | 0.744 (0.642, 0.836) | 0.746 (0.641, 0.838) |
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Peisen, F.; Gerken, A.; Hering, A.; Dahm, I.; Nikolaou, K.; Gatidis, S.; Eigentler, T.K.; Amaral, T.; Moltz, J.H.; Othman, A.E. Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors? Cancers 2024, 16, 2669. https://doi.org/10.3390/cancers16152669
Peisen F, Gerken A, Hering A, Dahm I, Nikolaou K, Gatidis S, Eigentler TK, Amaral T, Moltz JH, Othman AE. Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors? Cancers. 2024; 16(15):2669. https://doi.org/10.3390/cancers16152669
Chicago/Turabian StylePeisen, Felix, Annika Gerken, Alessa Hering, Isabel Dahm, Konstantin Nikolaou, Sergios Gatidis, Thomas K. Eigentler, Teresa Amaral, Jan H. Moltz, and Ahmed E. Othman. 2024. "Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors?" Cancers 16, no. 15: 2669. https://doi.org/10.3390/cancers16152669
APA StylePeisen, F., Gerken, A., Hering, A., Dahm, I., Nikolaou, K., Gatidis, S., Eigentler, T. K., Amaral, T., Moltz, J. H., & Othman, A. E. (2024). Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors? Cancers, 16(15), 2669. https://doi.org/10.3390/cancers16152669