Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome.

Background: The diagnosis of pelvic congestion syndrome (PCS) remains a challenge given the lack of universally accepted criteria. Although venography (VG) is the current gold standard for the diagnosis of PCS, non-invasive techniques like transvaginal ultrasonography (TVU) appear to be a valid alternative. The aim of this study was to design a predictive model for the venographic diagnostic of PCS using the parameters identified by TVU in patients with clinical suspicion of PCS, in order to individually assess the need to perform an invasive diagnostic and therapeutic technique such as VG. Methods: An observational and cross-sectional prospective study was conducted including 61 consecutively recruited patients with clinical suspicion of PCS, who were referred by the Pelvic Floor, Gynecology and Vascular Surgery Units, who were distributed in two groups: 18 belonging to the normal group and 43 to the PCS's group. We implemented and compared 19 binary logistic regression models, including the parameters that showed statistical significance in the prior univariate analysis. We evaluated individual predictive values with a receiver operating characteristic (ROC) curve and the area under the curve (AUC). Results: The selected model, based on the presence of pelvic veins or venous plexus of 8 mm or larger, observed by transvaginal ultrasound, had an AUC of 0.79 (95% CI: 0.63-0.96; P<0.001), with a sensitivity of 0.90 and specificity of 0.69, while the VG had a sensitivity of 86.05%, a specificity of 66.67%, and a positive predictive value of 86.05%. Conclusions: This assessment presents a feasible alternative that could potentially be added to our usual gynecological practice.

Can clinicopathological factors improve the prediction of metastasis to nonsentinel lymph nodes in patients with breast cancer?

INTRODUCTION: To determine whether clinicopathological characteristics can improve the prediction of metastasis to nonsentinel lymph nodes (NSLNs) over the use of only mRNA copy number in sentinel lymph node (SLN) biopsies. METHODS: This was a retrospective, observational study that included a total of 824 patients with T1-3 breast cancer who had clinically negative, ultrasound-negative axilla without evidence of metastasis and who underwent one-step nucleic acid amplification in SLN biopsies. RESULTS: 118 required a complete axillary lymph node dissection (ALNhD). About 35.6% (42/118) had metastases to a NSLN, and 64.4% (76/118) had no metastasis to a NSLN. The ROC curve of the total tumor load (TTL) presented an area under the curve (AUC) of 0.651 (95%; CI: 0.552-0.751). The 7294 copies of CK19 mRNA were established as the optimal cutoff point, with sensitivity: 93%, specificity: 63%, positive predictive value: 44%, and negative predictive value: 91%. By associating the clinicopathological parameters (multicentricity, pooled immunohistochemistry [IHC], and progesterone receptors), the AUC went up to 0.752 (95% CI: 0.663-0.841). CONCLUSIONS: Clinicopathological factors should be considered together with the total CK19 mRNA copy number (the TTL) of the SLNs to improve the predictive capacity of metastatic involvement of the NSLNs.

INTRODUCCIÓN: Nuestro objetivo era determinar si la influencia de las características clínicopatológicas pueden mejorar la predicción de metástasis en los ganglios linfáticos no centinelas (GLNC) a partir de un punto de corte de copias de ARNm determinado en la biopsia del ganglio linfático centinela (GLC). MÉTODOS: Se realizó un estudio observacional retrospectivo incluyendo a un total de 824 pacientes con cáncer de mama T1-3, con axila clínica y ecográficamente negativa para metástasis en los ganglios axilares. Se les practicó una biopsia selectiva del GLC y estudio posterior mediante el método one step nucleic acid amplification (OSNA). RESULTADOS: 118 precisaron una disección completa de los ganglios linfáticos axilares. 35,6% (42/118) tuvieron metástasis en GLNC y 64.4% (76/118) no presentaron metástasis en GLNC. La curva ROC del log de la carga tumoral total (CTT) presentó un área bajo la curva de 0.651 (95%; IC: 0.552-0.751). Se estableció las 7294 copias de ARNm de CK19 como punto de corte óptimo, con sensibilidad: 93%, especificidad: 63%, valor predictivo positivo: 44% y valor predictivo negativo: 91%. Al asociar los parámetros clinicopatológicos (multicentricidad, inmunohistoquímica (IHQ) agrupado y receptores de progesterona) obtenemos un área bajo la curva mejorada de 0.752 (95% intervalo de confianza [IC] 0.663-0.841). CONCLUSIONES: Los factores clinicopatológicos deberían valorarse asociados al corte de copias de ARNm de la CTT de CK19 de los GLCs para mejorar la capacidad predictiva de afectación metastásica en los GLNCs.

Identification of Pelvic Congestion Syndrome Using Transvaginal Ultrasonography. A Useful Tool.

The gold standard for the diagnosis of pelvic congestion syndrome (PCS) is venography (VG), although transvaginal ultrasound (TVU) might be a noninvasive, nonionizing alternative. Our aim is to determine whether TVU is an accurate and comparable diagnostic tool for PCS. An observational prospective study including 67 patients was carried out. A TVU was performed on patients, measuring pelvic venous vessels parameters. Subsequentially, a VG was performed, and results were compared for the test calibration of TVU. Out of the 67 patients included, only 51 completed the study and were distributed in two groups according to VG results: 39 patients belonging to the PCS group and 12 to the normal group. PCS patients had a larger venous plexus diameter (15.1 mm vs. 12 mm; p = 0.009) and higher rates of crossing veins in the myometrium (74.35% vs. 33.3%; p = 0.009), reverse or altered flow during Valsalva (58.9% vs. 25%; p = 0.04), and largest pelvic vein ≥ 8 mm (92.3% vs. 25%). The sensitivity and specificity of TVU were 92.3% (95% CI: 78.03-97.99%) and 75% (95% CI: 42.84-93.31%), respectively. In conclusion, transvaginal ultrasonography, with the described methodology, appears to be a promising tool for the diagnosis of PCS, with acceptable sensitivity and specificity.