Preoperative nomogram for individualized prediction of parametrial invasion in patients with FIGO stage IB cervical cancer treated with radical hysterectomy Tae-Wook Kong 1,2, Joo-Hyuk Son 1,2, Jiheum Paek 1,2, Yonghee Lee 1,3, Eun Ju Lee 1,4, Suk-Joon Chang 1,2, Hee-Sug Ryu 1,2 1 Gynecologic Cancer Center, Department of 2 Obstetrics and Gynecology, Department of 3 Pathology, and Department of 4 Radiology, Ajou University School of Medicine, Suwon, Korea
FIGO stage IB cervical cancer Piver type III radical hysterectomy (RH) Excellent local tumor control Long-term urologic complications (36%-47%) Sexual dysfunction Colorectal motility disorder Piver MS et al., 1974; Landoni F et al., 2001; Axelsen SM et al., 2006; Hazewinkel MH et al., 2010; Manchana T et al., 2010
Radical hysterectomy vs. radiation therapy FIGO stage IB-IIA, 343 patients randomized to either RH or radiation Survival: 83% (surgery) vs. 74% (radiation) Morbidity, esp., urologic complications 28% (RH) vs. 12% (radiation). P=0.0004 NCCN guidelines for FIGO stage IB2 chemoradiation (category 1), RH (category 2B) Treatment facilities, physician preference, costs, performance status Landoni F et al., 1997
Cost effectiveness and utility RH is cost effective for treating FIGO stage IB2 (vs. chemoradiation) Cost utility analysis Clinical and cost outcomes including survival, quality of life, cost of treating each complication RH plus adjuvant therapy Less cost effective Minimize postoperative chemoradiation Rocconi RP et al., 2005; Jewell EL et al., 2007; Katanyoo K et al., 2014; Cohn DE, 2014
Parametrial spread High-risk pathologic factors Positive margins, lymph node metastasis, parametrial invasion (PMI) Parametrial spread FIGO stage IB1 (5% - 10%), IB2/IIA2 (36.4%) cervical cancer Randomly located in the lateral and medial parametria Difficult to predict PMI for less radical surgery Girardi F et al., 1989; Landoni F et al., 1995; Benedetti-Panici P et al., 2000; Wright JD et al., 2007; Frumovitz M et al., 2009; Chang SJ et al., 2012; Park JY et al., 2013; Lee JY et al., 2014; Kong TW et al., 2014; Kato T et al., 2015; Kong TW et al., 2016
Clinical tumor size & SCC-Ag level (AUC = 0.789) Chang SJ et al., 2012
Pre-menopause Post-menopause MRI tumor size, SCC-Ag, Cyfra 21-1, Menopause (AUC = 0.858 in pre-menopause and 0.843 in post-menopause) Kong TW et al., 2016
Table. Correlation between SCC Ag and tumor volume measured by MRI in invasive cervical carcinoma Tumor volume (ml) Number of patients SCC Ag (ng/ml) < 2.0 7 0.7 ± 0.40 2.1-5.0 5 0.9 ± 0.37 5.1-10.0 5 3.0 ± 1.26 10.1-20.0 3 5.3 ± 0.88 20.1-50.0 9 7.5 ± 2.98 > 50.1 3 26.2 ± 15.83 γ 2 = 0.71, p = 0.01 Chung TY et al., 1996
Diameter-based ellipsoidal method Clinical tumor size MRI tumor size MRI tumor volume Hanato K et al., 1999; Mayr NA et al., 2002; Lee DW et al., 2010
Cervical stroma and tumor on T2-weighted MR images Tumor Intact cervical stromal ring Tumor Focal disruption of cervical stromal ring Radiological signs of PMI Disruption of cervical stromal ring High negative predictive value (94%-100%) Kim SH et al., 1990; Hricak H et al., 1998
Objectives To establish a preoperative nomogram predicting parametrial invasion by combining clinicopathologic factors in FIGO stage IB cervical cancer patients treated with radical hysterectomy
Total patients (n=360) Exclusion due to Conization (n=46) No SCC-Ag, Cyfra 21-1 (n=9) No MRI (n=5) Non-SCC, ASC, AC (n=2) Total enrolled patients (n=298) Figure 1. Inclusion criteria. SCC, squamous cell carcinoma; ASC, adenosquamous cell carcinoma; AC, adenocarcinoma; MRI, magnetic resonance imaging; SCC-Ag, squamous cell carcinoma-antigen; Cyfra 21-1, an enzyme immunoassay measuring serum fragments of cytokeratin 19.
Materials and methods Piver type III RH with retroperitoneal lymphadenectomy between February 2000 and March 2015 Retrospective review of clinicopathologic data of 298 patients with FIGO stage IB cervical cancer Nomogram Multivariate logistic regression analysis of preoperative clinicopathologic factors rms software package in R (https://www.r-project.org/)
Results
Table 1. Comparison of preoperative clinicopathologic factors between patients with and without microscopic parametrial invasion Factors Microscopic parametrial invasion Negative (n = 234) Positive (n = 64) p-value Age (year) 46.0 (24.0 72.0) 51.0 (27.0 68.0) 0.162 Parity 2 (0 5) 2 (0 6) 0.821 BMI (kg/m 2 ) 22.9 22.3 0.797 Surgical approach 0.176 ARH 156 (77.6) 45 (22.4) LRH 70 (83.3) 14 (16.7) RRH 8 (61.5) 5 (38.5) Histology 0.138 SCC 174 (78.7) 47 (21.3) AC 49 (83.1) 10 (16.9) ASC 11 (61.1) 7 (38.9) Grade 0.643 1 75 (80.6) 18 (19.4) 2 144 (78.3) 40 (21.7) 3 15 (71.4) 6 (28.6)
Table 1. Comparison of preoperative clinicopathologic factors between patients with and without microscopic parametrial invasion Factors Microscopic parametrial invasion Negative (n = 234) Positive (n = 64) p-value Menopasue 0.005 No 161 (83.4) 32 (16.6) Yes 73 (69.5) 32 (30.5) FIGO stage <0.001 IB1 200 (90.1) 22 (9.9) IB2 34 (44.7) 42 (55.3) Disruption of cervical stromal ring on MRI No 209 (93.7) 14 (6.3) Yes 25 (33.3) 50 (66.7) <0.001 Tumor volume on MRI (cm 3 ) 7.9 (0.5 65.4) 29.7 (3.0 84.6) <0.001 Serum SCC-Ag (ng/ml) 0.9 (0.2 20.7) 3.5 (0.1 43.9) <0.001 Serum Cyfra 21-1 (ng/ml) 1.1 (0.5 9.6) 2.3 (0.5 19.0) <0.001
Table 2. Multivariate analysis of preoperative clinicopathologic factors for predicting parametrial invasion Variables Disruption of cervical stromal ring on MRI Multivariate analysis Odds ratio (95% CI) p-value 10.201 (4.276 24.338) <0.001 Menopause 5.457 (2.080 14.319) 0.001 Serum SCC-Ag (ng/ml)* 1.164 (1.050 1.250) 0.004 Tumor volume on MRI (cm 3 )* 1.068 (1.034 1.102) <0.001 *Continuous variables
Hosmer Lemeshow test, p = 0.314
Table 3. Predicted probability of parametrial invasion and actual parametrial invasion rate according to risk groups Low-risk group High-risk group Predefined predicted probability of PMI (%) <10 10 Total score (points) <38 38 Number of patients 200 98 Predicted probability of PMI (%) 3.5 58.2 Actual PMI rate (%) 2.5 (5 out of 200 patients) 60.2 (59 out of 98 patients)
Conclusions We developed a preoperative nomogram predicting PMI in surgically-treated FIGO stage IB cervical cancer patients In terms of the costs and utility of treatment, the use of postoperative chemoradiation should be minimized The probabilities from this nomogram may have the potential to provide valuable guidance for physicians regarding the primary management in FIGO stage IB cervical cancer patients
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