A Nomogram Model Based on Neuroendocrine Markers for Predicting the Prognosis of Neuroendocrine Carcinoma of Cervix
<p>The nomogram model for predicting the recurrence-free survival of neuroendocrinal carcinoma of cervix after surgery. (Each variable from the second row to the seventh row corresponds to a point value in the first row “point”. Then, sum the scores of each variable to obtain the “total point”, and finally derive 1-year, 2-year, 3-year and 5-year recurrence-free survival (RFS)).</p> "> Figure 2
<p>(<b>a</b>) The calibration curves of this nomogram model for predicting recurrence-free survival of neuroendocrinal carcinoma of cervix in the training cohort. (<b>b</b>) The calibration curves of this nomogram model for predicting recurrence-free survival of neuroendocrinal carcinoma of cervix in the validated cohort. (The dotted line: reference line. The solid line: the prediction curve provided by the nomogram model).</p> "> Figure 3
<p>The ROC curve of the optimal threshold of 3–year recurrence-free survival based on the established nomogram model. (Black dot: the area under the curve (AUC) at this point is the largest, which indicates the optimal threshold value of the 3-year recurrence-free survival predicted by the model is 0.85 (sensitivity, 82.6%; specificity, 89.2%; area under the curve = 0.895; 95% CI 0.808–0.983). Dotted line: reference line. Solid line: the ROC curve of the established nomogram model).</p> "> Figure 4
<p>(<b>a</b>) Kaplan–Meier survival curves of recurrence-free survival between the low-RFS group and the high-RFS group. (<b>b</b>) Kaplan–Meier survival curves of overall survival between the low-RFS group and the high-RFS group. ((<b>a</b>) Solid line: the recurrence-free survival curve of the high-RFS group. Dotted line: the recurrence-free survival of the curve of the low-RFS group. (<b>b</b>) The solid line: The overall survival curve of the high-RFS group. The dotted line: The overall survival of curve the low-RFS group).</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Population
2.2. Immunohistochemistry
2.3. Follow-Up and Recurrence
2.4. Statistical Analysis
3. Results
3.1. Clinicopathological Characteristics of Patints
3.1.1. Factors Related to Recurrence of Cervical Neuroendocrine Carcinoma
3.1.2. Predictive Nomogram Model for Cancer Recurrence
3.1.3. Optimal Threshold of Recurrence-Free Survival Rate of Nomogram Model
4. Discussion
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variable | Training Cohort | % | Validation Cohort | % | p Value |
---|---|---|---|---|---|
N = 171 | N = 86 | ||||
Age median (years); | 0.399 | ||||
Mean ± SD | 45.92 ± 9.991 | 44.91 ± 10.104 | |||
Median (range) | 46 (25–75) | 45 (25–75) | |||
BMI (kg/m2); | 0.781 | ||||
Mean ± SD | 22.81 ± 2.976 | 22.73 ± 2.605 | |||
Median (range) | 22.30 (18–39) | 22 (18–32) | |||
FIGO stage | 0.582 | ||||
I | 111 | 64.9 | 51 | 59.3 | |
II | 24 | 14.0 | 16 | 18.6 | |
III | 36 | 21.1 | 19 | 22.1 | |
Pathological type | 0.527 | ||||
LG-NECC | 21 | 12.3 | 13 | 15.1 | |
HG-NECC | 150 | 87.7 | 73 | 84.9 | |
Stromal invasion | 0.567 | ||||
<1/2 | 86 | 50.3 | 40 | 46.5 | |
≥1/2 | 85 | 49.7 | 46 | 53.5 | |
Endometrial invasion | 0.912 | ||||
Yes | 23 | 13.5 | 12 | 14.0 | |
No | 148 | 86.5 | 74 | 86.0 | |
Nerve invasion | |||||
Yes | 14 | 8.2 | 8 | 9.3 | 0.763 |
No | 157 | 91.8 | 78 | 90.7 | |
C-UJI | 0.168 | ||||
Yes | 40 | 23.4 | 27 | 31.4 | |
No | 131 | 76.6 | 59 | 68.6 | |
LVI | 0.681 | ||||
Yes | 45 | 26.3 | 22 | 25.6 | |
No | 126 | 73.7 | 64 | 74.4 | |
LVSI | 0.135 | ||||
Yes | 123 | 71.9 | 54 | 62.8 | |
No | 48 | 28.1 | 32 | 37.2 | |
HPV | |||||
negative | 81 | 47.4 | 37 | 43.0 | 0.509 |
positive | 90 | 52.6 | 49 | 57.0 | |
P16 | 0.681 | ||||
0 | 21 | 12.3 | 13 | 15.1 | |
1+ | 80 | 46.8 | 44 | 51.2 | |
2+ | 12 | 7.0 | 4 | 4.7 | |
3+ | 58 | 33.9 | 25 | 29.1 | |
Syn | 0.293 | ||||
0 | 17 | 9.9 | 14 | 16.3 | |
1+ | 94 | 55.0 | 48 | 55.8 | |
2+ | 41 | 24.0 | 19 | 22.1 | |
3+ | 19 | 11.1 | 5 | 5.8 | |
CgA | 0.523 | ||||
0 | 53 | 31.0 | 20 | 23.3 | |
1+ | 72 | 42.1 | 42 | 48.8 | |
2+ | 21 | 12.3 | 9 | 10.5 | |
3+ | 25 | 14.6 | 15 | 17.4 | |
CD56 | 0.722 | ||||
0 | 46 | 26.9 | 20 | 23.3 | |
1+ | 71 | 41.5 | 42 | 48.8 | |
2+ | 14 | 8.2 | 7 | 8.1 | |
3+ | 40 | 23.4 | 17 | 19.8 | |
Recurrence | 0.122 | ||||
Yes | 23 | 13.5 | 18 | 20.9 | |
No | 148 | 86.5 | 68 | 79.1 | |
Death | 0.669 | ||||
Yes | 21 | 12.3 | 9 | 10.5 | |
No | 150 | 87.7 | 77 | 89.5 | |
RFS (months) | 0.815 | ||||
Median | 42 | 37.5 | |||
Mean ± SD | 52.73 ± 42.892 | 54.51 ± 43.767 | |||
Range | 2–150 | 4–145 | |||
Follow-up (months) | 0.803 | ||||
Median | 44 | 38 | |||
Mean ± SD | 54.19 ± 41.232 | 54.51 ± 43.763 | |||
Range | 2–150 | 4–145 |
Variable | Univariate Analysis | Multivariate Analysis | ||||
---|---|---|---|---|---|---|
HR | 95% CI | p Value | HR | 95% CI | p Value | |
FIGO stage | ||||||
I | 1.000 | p < 0.001 | 1.000 | 0.023 | ||
II | 3.903 | 1.100–13.847 | 0.035 | 8.868 | 1.523–15.652 | 0.015 |
III | 8.718 | 3.305–15.996 | p < 0.001 | 5.628 | 1.126–12.128 | 0.035 |
Stromal invasion (<1/2 vs. ≥1/2) | 3.715 | 1.132–3.176 | 0.009 | 9.898 | 2.309–42.429 | 0.002 |
Nerve invasion (Yes vs. No) | 3.367 | 1.131–10.024 | 0.029 | 1.185 | 0.144–9.776 | 0.875 |
LVSI (Yes vs. No) | 4.857 | 1.138–20.727 | 0.033 | 7.077 | 1.099–5.564 | 0.039 |
LVI (Yes vs. No) | 3.848 | 1.693–8.748 | 0.001 | 6.235 | 1.360–8.576 | 0.018 |
C-UJI (Yes vs. No) | 3.466 | 1.513–7.938 | 0.003 | 8.693 | 2.606–15.445 | 0.005 |
CgA | ||||||
0 | 1.000 | 0.003 | 1.000 | 0.021 | ||
1+ | 6.300 | 0.788–5.380 | 0.083 | 6.302 | 1.143–6.841 | 0.040 |
2+ | 8.442 | 1.570–15.095 | 0.018 | 7.772 | 1.149–7.462 | 0.040 |
3+ | 9.673 | 2.933–17.216 | 0.003 | 9.362 | 4.304–10.180 | 0.003 |
Variable | Training Cohort | Validation Cohort | ||
---|---|---|---|---|
C-Index | 95% CI | C-Index | 95% CI | |
FIGO stage, stromal invasion, lymph vascular space invasion, lymph node involvement, cervical uterine junction invasion | 0.829 | 0.747–0.911 | 0.883 | 0.756–1.010 |
FIGO stage, stromal invasion, lymph vascular space invasion, lymph node involvement, cervical uterine junction invasion, CgA | 0.863 | 0.784–0.942 | 0.884 | 0.758–1.010 |
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Jia, M.; Pi, J.; Zou, J.; Feng, M.; Chen, H.; Lin, C.; Yang, S.; Deng, Y.; Xiao, X. A Nomogram Model Based on Neuroendocrine Markers for Predicting the Prognosis of Neuroendocrine Carcinoma of Cervix. J. Clin. Med. 2023, 12, 1227. https://doi.org/10.3390/jcm12031227
Jia M, Pi J, Zou J, Feng M, Chen H, Lin C, Yang S, Deng Y, Xiao X. A Nomogram Model Based on Neuroendocrine Markers for Predicting the Prognosis of Neuroendocrine Carcinoma of Cervix. Journal of Clinical Medicine. 2023; 12(3):1227. https://doi.org/10.3390/jcm12031227
Chicago/Turabian StyleJia, Mingzhu, Jiangchuan Pi, Juan Zou, Min Feng, Huiling Chen, Changsheng Lin, Shuqi Yang, Ying Deng, and Xue Xiao. 2023. "A Nomogram Model Based on Neuroendocrine Markers for Predicting the Prognosis of Neuroendocrine Carcinoma of Cervix" Journal of Clinical Medicine 12, no. 3: 1227. https://doi.org/10.3390/jcm12031227