Prediction of Early Distant Recurrence in Upfront Resectable Pancreatic Adenocarcinoma: A Multidisciplinary, Machine Learning-Based Approach
Abstract
:Simple Summary
Abstract
1. Introduction
2. Methods
2.1. Patients’ Cohort
2.2. Surgical Technique, Pathology Protocol, Adjuvant Therapy and Follow-Up Data Collection
2.3. Clinical Variables
2.4. Radiological Variables and Radiomic Features
2.5. Statistical Analysis
3. Results
3.1. Patients’ Cohort
3.2. Variables Selection
3.3. Training and Validation of the Radiomic Model
3.4. Training and Validation of the Clinicoradiological Model
3.5. Training and Validation of the Combined Model
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Total (n = 147) | Training (n = 94) | Validation (n = 53) | p-Value | ||
---|---|---|---|---|---|
Clinical Variables | Age at diagnosis (year) * | 69.94 (44–88) | 70.06 (43–87) | 69.73 (43–88) | 0.84 |
Sex | 0.13 | ||||
Female | 61 (41.6%) | 35 (37.6%) | 27 (50.5%) | ||
Male | 86 (58.4%) | 59 (63.4%) | 26 (49.5%) | ||
Ca 19.9 (U/mL) * | 40 (14–150) | 48.5 (13.25–191) | 35 (14.5–77.5) | 0.21 | |
Adjuvant Treatment | 111 (75%) | 69 (73.2%) | 42 (78.6%) | 0.38 | |
Adjuvant Chemoterapy | 107 (73.0%) | 68 (73.0%) | 39 (73.2%) | 0.45 | |
Adjuvant Radioteraphy | 31 (21%) | 21 (22.3%) | 10 (19.6%) | 0.11 | |
Pathological Data | Tumor Size (mm) ^ | 27.33 (+/− 0.78) | 28.36 (+/− 0.97) | 25.48 (+/− 1.29) | 0.78 |
Final R status | 0.08 | ||||
R1 | 65 (44.2%) | 44 (46.8%) | 21 (39.6%) | ||
R0 | 82 (55.8%) | 50 (53.2%) | 32 (60.4%) | ||
Lymph-vascular Invasion | 129 (87.8%) | 88 (93.6%) | 41 (76.8%) | 0.015 | |
Perineural Invasion | 130 (87.1%) | 86 (91.4%) | 44 (82.1%) | 0.06 | |
Peripancreatic Fat Invasion | 135 (91%) | 92 (97.8%) | 43 (80.3%) | 0.72 | |
Grading | 0.42 | ||||
G1 | 3 (2.0%) | 3 (3.1%) | 0 (0%) | ||
G2 | 66 (45.0%) | 45 (47.8%) | 26 (48.2%) | ||
G3 | 78 (53.0%) | 46 (49.1%) | 27 (51.8%) | ||
TNM | |||||
T | 0.75 | ||||
T1 | 34 (22.7%) | 20 (20.3%) | 14 (26.8%) | ||
T2 | 102 (69.2%) | 68 (72.3%) | 34 (64.3%) | ||
T3 | 11 (7.7%) | 7 (7.4%) | 5 (8.9%) | ||
N | 0.065 | ||||
N0 | 23 (16.1%) | 15 (15.0%) | 9 (17.8%) | ||
N1 | 50 (33.9%) | 26 (27.6%) | 24 (44.6%) | ||
N2 | 74 (50%) | 54 (57.4%) | 20 (37.5%) | ||
Lymphnode Ratio * | 0.136 (0.04–0.25) | 0.16 (0.06–0.26) | 0.10 (0.03–0.2) | 0.11 | |
Radiological Data | Dimension (mm) ^ | 24.5 (+/− 7.2) | 25.79 (+/− 6.8) | 23.23 (+/− 7.8) | 0.07 |
Necrosis | 0.34 | ||||
Present | 27 (18.2%) | 18 (19.1%) | 9 (16.9%) | ||
Absent | 120 (81.6%) | 76 (85.2%) | 44 (83.0%) | ||
Hypodense on pancreatic phase | 116 (74.4%) | 77 (81.9%) | 39 (73.5%) | 0.48 | |
Hypodense on venous phase | 93 (57.1%) | 91 (96.8%) | 2 (3.5%) | 0.50 | |
Isodense on pancreatic phase | 23 (21.8%) | 21 (23.4%) | 2 (3.5%) | 0.58 | |
Outcome Variables | Early distant recurrence (EDR) | 0.54 | |||
EDR | 39 (25.6%) | 25 (26.5%) | 14 (26.3%) | ||
non-EDR | 108 (74.4%) | 69 (73.5%) | 39 (73.7%) | ||
Time to recurrence (months) * | 15 (10–22) | 15 (9–22) | 16 (11–26) | 0.55 | |
Overall survival (months) * | 20 (15–28) | 20 (15–28) | 20 (16–28.5) | 0.98 | |
Length of follow-up (months) * | 19 (14–27) | 19 (14–27) | 19.5 (13.25–27.75) | 0.94 |
Radomic Model | Coefficient | p-value | OR | 95%CI | Overall Fit Model | AUC | 95%CI | Sensivity | Specifity | PPP | NPP | ||||||||
Surface To Volume Ratio | −3.82224 | 0.0183 | 0.0219 | 0.0009 to 0.5237 | 0.0097 | 0.0244 | 0.599 | 0.733 | 0.493 to 0.699 | 0.593 to 0.846 | 90.9 | 100.0 | 23.08 | 26.2 | 62.5 | 24.4 | 64.3 | 100.0 | |
Clinico Radiological Model | Coefficient | p-value | OR | 95%CI | Overall Fit Model | AUC | 95%CI | Sensivity | Specifity | PPP | NPP | ||||||||
Ca19.9 | 0.001128 | 0.049 | 1.0011 | 1.0000 to 1.0023 | 0.0018 | 0.9529 | 0.72 | 0.536 | 0.614 to 0.811 | 0.392 to 0.675 | 68.9 | 20.0 | 76.27 | 73.8 | 58.8 | 15.4 | 83.3 | 79.5 | |
Necrosis | 1.10839 | 0.0633 | 3.0295 | 0.9402 to 9.7611 | |||||||||||||||
Combined Model | Coefficient | p-value | OR | 95%CI | Overall Fit Model | AUC | 95%CI | Sensivity | Specifity | PPP | NPP | ||||||||
Ca19.9 | 0.000964 | 0.0946 | 1.011 | 0.9998 to 1.0021 | 0.0015 | 0.0178 | 0.736 | 0.76 | 0.648 to 0.838 | 0.618 to 0.865 | 58.6 | 60.0 | 86.44 | 78.5 | 68.0 | 40.0 | 81.0 | 89.2 | |
Necrosis | 0.86465 | 0.1594 | 2.3742 | 0.7120 to 7.9167 | |||||||||||||||
Surface To Volume Ratio | −2.8972 | 0.1171 | 0.0552 | 0.0015 to 2.0684 | |||||||||||||||
Training | |||||||||||||||||||
Validation |
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Share and Cite
Palumbo, D.; Mori, M.; Prato, F.; Crippa, S.; Belfiori, G.; Reni, M.; Mushtaq, J.; Aleotti, F.; Guazzarotti, G.; Cao, R.; et al. Prediction of Early Distant Recurrence in Upfront Resectable Pancreatic Adenocarcinoma: A Multidisciplinary, Machine Learning-Based Approach. Cancers 2021, 13, 4938. https://doi.org/10.3390/cancers13194938
Palumbo D, Mori M, Prato F, Crippa S, Belfiori G, Reni M, Mushtaq J, Aleotti F, Guazzarotti G, Cao R, et al. Prediction of Early Distant Recurrence in Upfront Resectable Pancreatic Adenocarcinoma: A Multidisciplinary, Machine Learning-Based Approach. Cancers. 2021; 13(19):4938. https://doi.org/10.3390/cancers13194938
Chicago/Turabian StylePalumbo, Diego, Martina Mori, Francesco Prato, Stefano Crippa, Giulio Belfiori, Michele Reni, Junaid Mushtaq, Francesca Aleotti, Giorgia Guazzarotti, Roberta Cao, and et al. 2021. "Prediction of Early Distant Recurrence in Upfront Resectable Pancreatic Adenocarcinoma: A Multidisciplinary, Machine Learning-Based Approach" Cancers 13, no. 19: 4938. https://doi.org/10.3390/cancers13194938