A comparison of CA125, HE4, risk ovarian malignancy algorithm (ROMA), and risk malignancy index (RMI) for the classification of ovarian masses

OBJECTIVE: Differentiation between benign and malignant ovarian neoplasms is essential for creating a system for patient referrals. Therefore, the contributions of the tumor markers CA125 and human epididymis protein 4 (HE4) as well as the risk ovarian malignancy algorithm (ROMA) and risk malignancy index (RMI) values were considered individually and in combination to evaluate their utility for establishing this type of patient referral system. METHODS: Patients who had been diagnosed with ovarian masses through imaging analyses (n = 128) were assessed for their expression of the tumor markers CA125 and HE4. The ROMA and RMI values were also determined. The sensitivity and specificity of each parameter were calculated using receiver operating characteristic curves according to the area under the curve (AUC) for each method. RESULTS: The sensitivities associated with the ability of CA125, HE4, ROMA, or RMI to distinguish between malignant versus benign ovarian masses were 70.4%, 79.6%, 74.1%, and 63%, respectively. Among carcinomas, the sensitivities of CA125, HE4, ROMA (pre-and post-menopausal), and RMI were 93.5%, 87.1%, 80%, 95.2%, and 87.1%, respectively. The most accurate numerical values were obtained with RMI, although the four parameters were shown to be statistically equivalent. CONCLUSION: There were no differences in accuracy between CA125, HE4, ROMA, and RMI for differentiating between types of ovarian masses. RMI had the lowest sensitivity but was the most numerically accurate method. HE4 demonstrated the best overall sensitivity for the evaluation of malignant ovarian tumors and the differential diagnosis of endometriosis. All of the parameters demonstrated increased sensitivity when tumors with low malignancy potential were considered low-risk, which may be used as an acceptable assessment method for referring patients to reference centers.

Transmission of clear cell tumor in a graft liver from cadaveric donor: Case report

Neoplasms in children after organ transplantation are related to the type and intensity of immunosuppression and the donorrecipient serostatus, especially in relation to the EpsteinBarr virus. The patient was a two-yr-old female child with biliary atresia who underwent a liver transplantation from a female cadaver donor. Two adults received kidney transplants from the same donor. Nine months after transplantation, one of the adult recipients developed an urothelial tumor in the kidney graft. Imaging tests were repeated monthly in the liver-transplanted child and revealed no abnormalities. However, one yr and two months after the transplantation, the patient developed episodes of fever. At that time, imaging and liver biopsy showed a clear cell tumor of urothelial origin in the graft and the disease was limited to the liver. The patient underwent liver retransplantation, and she is currently free of tumor recurrence. Although rare, the occurrence of tumors in the post-transplant period from cadaver donors, without previously diagnosed tumors, is one of the many problems encountered in the complex world of organ transplantation.

De Novo Thrombotic Microangiopathy After Kidney Transplantation: Clinical Features, Treatment, and Long-Term Patient and Graft Survival

Introduction. Posttransplant thrombotic microangiopathy (TMA)/hemolytic uremic syndrome (HUS) can occur as a recurrent or de novo disease. Methods. A retrospective single-center observational study was applied in order to examine the incidence and outcomes of de novo TMA/HUS among transplantations performed between 2000 and 2010. Recurrent HUS or antibody-mediated rejections were excluded. Results. Seventeen (1.1%) among 1549 kidney transplant recipients fulfilled criteria for de novo TMA. The mean follow-up was 572 days (range, 69-1769). Maintenance immunosuppression was prednisone, tacrolimus (TAC), and mycophenolic acid in 14 (82%) patients. Mean age at onset was 40 +/- 15 years, and serum creatinine was 6.1 +/- 4.1 mg/dL. TMA occurred at a median of 25 days (range, 1-1755) after transplantation. Nine (53%) patients developed TMA within 1 month of transplantation and only 12% after 1 year. Clinical features were anemia (hemoglobin < 10 g/dL) in 9 (53%) patients, thrombocytopenia in 7 (41%), and increased lactate dehydrogenase in 12 (70%). Decreased haptoglobin was observed in 64% and schistocytes in 35%. Calcineurin inhibitor (CM) withdrawal or reduction was the first step in the management of 10/15 (66%) patients, and 6 (35%) received fresh frozen plasma (FFP) and/or plasmapheresis. TAC was successfully reintroduced in six patients after a median of 17 days. Eight (47%) patients needed dialytic support after TMA diagnosis and 75% remained on dialysis. At 4 years of follow-up, death-censored graft survival was worse for TMA group (43.0% versus 85.6%, log-rank = 0.001; hazard ratio = 3.74) and there was no difference in patient survival (53.1% versus 82.2%, log-rank = 0.24). Conclusion. De novo TMA after kidney transplantation is a rare but severe condition with poor graft outcomes. This syndrome may not be fully manifested, and clinical suspicion is essential for early diagnosis and treatment, based mainly in CM withdrawal and FFP infusions and/or plasmapheresis.

Risk Factors and Survival Impact of Primary Graft Dysfunction After Lung Transplantation in a Single Institution

Background. Lung transplantation has become a standard procedure for some end-stage lung diseases, but primary graft dysfunction (PGD) is an inherent problem that impacts early and late outcomes. The aim of this study was to define the incidence, risk factors, and impact of mechanical ventilation time on mortality rates among a retrospective cohort of lung transplantations performed in a single institution. Methods. We performed a retrospective study of 118 lung transplantations performed between January 2003 and July 2010. The most severe form of PGD (grade III) as defined at 48 and 72 hours was examined for risk factors by multivariable logistic regression models using donor, recipient, and transplant variables. Results. The overall incidence of PGD at 48 hours was 19.8%, and 15.4% at 72 hours. According multivariate analysis, risk factors associated with PGD were donor smoking history for 48 hours (adjusted odds ratio [OR], 4.83; 95% confidence interval [CI], 1.236-18.896; P = .022) and older donors for 72 hours (adjusted OR, 1.046; 95% CI, 0.997-1.098; P = .022). The operative mortality was 52.9% among patients with PGD versus 20.3% at 48 hours (P = .012). At 72 hours, the mortality rate was 58.3% versus 21.2% (P = .013). The 90-days mortality was also higher among patients with PGD. The mechanical ventilation time was longer in patients with PGD III at 48 hours namely, a mean time of 72 versus 24 hours (P = .001). When PGD was defined at 72 hours, the mean ventilation time was even longer, namely 151 versus 24 hours (P < .001). The mean overall survival for patients who developed PGD at 48 hours was 490.9 versus 1665.5 days for subjects without PGD (P = .001). Considering PGD only at 72 hours, the mean survival was 177.7 days for the PGD group and 1628.9 days for the other patients (P < .001). Conclusion. PGD showed an important impacts on operative and 90-day mortality rates, mechanical ventilation time, and overall survival among lung transplant patients. PGD at 72 hours was a better predictor of lung transplant outcomes than at 48 hours. The use of donors with a smoking history or of advanced age were risk factors for the development of PGD.