Axillary Lymph Node Dissection for Sentinel Lymph Node Micrometastases May Be Safely Omitted in Early-Stage Breast Cancer Patients: Long-Term Outcomes of a Prospective Study.

OBJECTIVES: To evaluate the long-term disease-free and overall survival of patients with sentinel lymph node (SLN) micrometastases, in whom a completion axillary lymph node dissection (ALND) was systematically omitted. BACKGROUND: The use of step sectioning and immunohistochemistry for SLN analysis results in a more accurate histopathologic examination and a higher detection rate of micrometastases. However, the clinical relevance and therapeutic implications of SLN micrometastases remain a matter of debate. METHODS: In this prospective study, 236 SLN biopsies were performed in 234 consecutive early-stage breast cancer patients (T1, T2 </= 3 cm, cN0 M0) between 1998 and 2002. The SLN were examined by step sectioning and stained with hematoxylin and eosin and immunohistochemistry. None of the patients with negative SLN or SLN micrometastases (International Union Against Cancer classification, >.2 mm to </=2 mm) underwent a completion ALND or radiation to the axilla. Long-term overall and disease-free survivals were compared between patients with negative SLN and those with SLN micrometastases by log rank tests. RESULTS: The SLN was negative in 55% of patients (123 of 224). SLN micrometastases were detected in 27 patients (27 of 224, 12%). After a median follow-up of 77 months (range, 24-106 months), neither locoregional recurrences nor distant metastases occurred in any of the 27 patients with SLN micrometastases. There were no statistically significant differences for overall (P = .656), locoregional (P = .174), and axillary and distant disease-free survival (P = .15) between patients with negative SLN and SLN micrometastases. CONCLUSIONS: This analysis of unselected patients provides evidence that a completion level I and II ALND may be safely omitted in early-stage breast cancer patients with SLN micrometastases.

Morbidity, survival, and site of recurrence after mediastinal lymph-node dissection versus systematic sampling after complete resection for non-small cell lung cancer

BACKGROUND: Mediastinal lymph-node dissection was compared to systematic mediastinal lymph-node sampling in patients undergoing complete resection for non-small cell lung cancer with respect to morbidity, duration of chest tube drainage and hospitalization, survival, disease-free survival, and site of recurrence. METHODS: A consecutive series of one hundred patients with non-small-cell lung cancer, clinical stage T1-3 N0-1 after standardized staging, was divided into two groups of 50 patients each, according to the technique of intraoperative mediastinal lymph-node assessment (dissection versus sampling). Mediastinal lymph-node dissection consisted of removal of all lymphatic tissues within defined anatomic landmarks of stations 2-4 and 7-9 on the right side, and stations 4-9 on the left side according to the classification of the American Thoracic Society. Systematic mediastinal lymph-node sampling consisted of harvesting of one or more representative lymph nodes from stations 2-4 and 7-9 on the right side, and stations 4-9 on the left side. RESULTS: All patients had complete resection. A mean follow-up time of 89 months was achieved in 92 patients. The two groups of patients were comparable with respect to age, gender, performance status, tumor stage, histology, extent of lung resection, and follow-up time. No significant difference was found between both groups regarding the duration of chest tube drainage, hospitalization, and morbidity. However, dissection required a longer operation time than sampling (179 +/- 38 min versus 149 +/- 37 min, p < 0.001). There was no significant difference in overall survival between the two groups; however, patients with stage I disease had a significantly longer disease-free survival after dissection than after sampling (60.2 +/- 7 versus 44.8 +/- 8 months, p < 0.03). Local recurrence was significantly higher after sampling than after dissection in patients with stage I tumor (12.5% versus 45%, p = 0.02) and in patients with nodal tumor negative mediastinum (N0/N1 disease) (46% versus 13%, p = 0.004). CONCLUSION: Our results suggest that mediastinal lymph-node dissection may provide a longer disease-free survival in stage I non-small cell lung cancer and, most importantly, a better local tumor control than mediastinal lymph-node sampling after complete resection for N0/N1 disease without leading to increased morbidity.

Combined radiohormonotherapy in node positive lymph node prostate cancer

Purpose: Pelvic radiation therapy (RT) represents a therapeutic option in the treatment of node-positive prostate cancer but it remains controversial, because of its high rate toxicities. New radiation technique such as IMRT may reduce these complications. In this study, we aimed to assess the rate of toxicities according to CTC-NCI.v3 in such patients treated with either 3DCRT or IMRT (Tomotherapy).Methods and Materials: From January 2008 to December 2010, data were analyzed from 30 consecutive patients including 29 node-positive prostate cancer undergoing definitive or adjuvant RT (IMRT and/or 3DCRT) after radical prostatectomy and lymphadenectomy combined to hormonal therapy. Median age was 66 years (range : 52-83). Median preoperative PSA value was 12 ng/ml (range: 2.72-165). According to the pT-classification, there were 4 pT2, 7 pT3a, 10 pT3b, and 1 pT4 patients. Pathologic positive lymph nodes were found in 23 patients. Radiologic positive lymph nodes were found in 5 patients. Two patients were node negative. Gleason score was ranging between 7 to 10. Twelve patients were treated by Tomotherapy including 4 with simultaneous integrated boost (SIB). Eighteen patients were treated by Tomotherapy including 2 with SIB to the whole pelvis and 3DCRT boost to the prostate. V50% for bladder and rectum were recorded. Acute and late toxicities were assessed according to CTC-NCI.v3 classification.Results: With a median follow-up of 17 months, only one patient presented nodal and metastatic failure. Urinary incontinence was graded 1 after surgery for 6 patients and grade 2 in two. Sexual impuissance was noted in 3 patients. Acute toxicities during RT were proctitis grade 0 in 23 patients (76.5%), grade 1 in 7 (23.5%). Nocturia grade 1 in 9 patients. Interruption of treatment was seen in only case because of grade 3 urinary incontinence. Late effects included erectile dysfunction in 5 patients (83%) and one patient had grade 3proctitis requiring colostomy 3 months after RT. Median Dose-Volume Histogram according to radiation techniques V50% bladder V50% rectum Tomotherapy (IMRT) 36.25 Gy 39 Gy Tomotherapy + 3DCRT 41.26 Gy 39.18 GyConclusion: Based on our above-mentioned findings, there is no a significant difference in morbidity in patients treated with Tomotherapy or Tomotherapy with 3DCRT boost.

Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer.

BACKGROUND: A 70-gene signature was previously shown to have prognostic value in patients with node-negative breast cancer. Our goal was to validate the signature in an independent group of patients. METHODS: Patients (n = 307, with 137 events after a median follow-up of 13.6 years) from five European centers were divided into high- and low-risk groups based on the gene signature classification and on clinical risk classifications. Patients were assigned to the gene signature low-risk group if their 5-year distant metastasis-free survival probability as estimated by the gene signature was greater than 90%. Patients were assigned to the clinicopathologic low-risk group if their 10-year survival probability, as estimated by Adjuvant! software, was greater than 88% (for estrogen receptor [ER]-positive patients) or 92% (for ER-negative patients). Hazard ratios (HRs) were estimated to compare time to distant metastases, disease-free survival, and overall survival in high- versus low-risk groups. RESULTS: The 70-gene signature outperformed the clinicopathologic risk assessment in predicting all endpoints. For time to distant metastases, the gene signature yielded HR = 2.32 (95% confidence interval [CI] = 1.35 to 4.00) without adjustment for clinical risk and hazard ratios ranging from 2.13 to 2.15 after adjustment for various estimates of clinical risk; clinicopathologic risk using Adjuvant! software yielded an unadjusted HR = 1.68 (95% CI = 0.92 to 3.07). For overall survival, the gene signature yielded an unadjusted HR = 2.79 (95% CI = 1.60 to 4.87) and adjusted hazard ratios ranging from 2.63 to 2.89; clinicopathologic risk yielded an unadjusted HR = 1.67 (95% CI = 0.93 to 2.98). For patients in the gene signature high-risk group, 10-year overall survival was 0.69 for patients in both the low- and high-clinical risk groups; for patients in the gene signature low-risk group, the 10-year survival rates were 0.88 and 0.89, respectively. CONCLUSIONS: The 70-gene signature adds independent prognostic information to clinicopathologic risk assessment for patients with early breast cancer.

Urban image classification with semisupervised multiscale cluster kernels

This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

Sentinel nodes and and non sentinel nodes evaluation in T1 melanoma patients

Objective: Because increasing incidence of melanoma and dermatologicsystematic screening, more early superficial melanoma are discovered in Switzerland. Patients with Breslow index more than 1 mm. (T2) represent the classical indication to sentinel node (SN). It has been shown that some ''risky'' T1 patients may have micrometastatic SNs. T1b melanoma are defined by presence of ulceration,Clark IV (ormore) level, signs of melanoma regression (old classification) and high mitotic index (new TNM). The objective of the present study was to review the incidence and risk for metastatic SN in T1 patients and if radical lymph node dissection is justified (evaluation of non sentinel node [NSN]) compared with T2-4 patients.Methods: Retrospective review of a cohort of all patients operated for T1-4 clinically N0 and radiological M0 melanoma patients between 1997 and 2010 in a reference melanoma centre.Results: 599 melanoma patients have been operated with SNdissection. There were 98 T1 patients. Metastatic SN were observed in 2 out of 24 T1a patients and in 5 out of 74 T1b patients. This means overall 7% T1 patients were at least N1a. None of SN+ T1a or T1b patients had metastatic NSN after radical lymph node dissections (RLND). During the follow-up (1998-2010), no patients presented with locoregional disease and only one T1a N1a patient died of metastatic melanoma. These results contrast with the other 591 T2-4 patients: 150 were SN+ (25%) and among them 23 had metastatic NSN after RLND. Overall 23/136 (17%) had metastatic NSN.Conclusion: T1 melanoma patients are at significant risk (7%) for metastatic lymph node in the corresponding drainage basin. T1a and T1b did not differ regarding this risk. However, the benefit for a RLND must be reevaluated regarding surgical morbidity, because none of T1 patients had metastatic NSN.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Prognostic value of sentinel node biopsy in 327 prospective melanoma patients from a single institution

AIM: To confirm the accuracy of sentinel node biopsy (SNB) procedure and its morbidity, and to investigate predictive factors for SN status and prognostic factors for disease-free survival (DFS) and disease-specific survival (DSS). MATERIALS AND METHODS: Between October 1997 and December 2004, 327 consecutive patients in one centre with clinically node-negative primary skin melanoma underwent an SNB by the triple technique, i.e. lymphoscintigraphy, blue-dye and gamma-probe. Multivariate logistic regression analyses as well as the Kaplan-Meier were performed. RESULTS: Twenty-three percent of the patients had at least one metastatic SN, which was significantly associated with Breslow thickness (p<0.001). The success rate of SNB was 99.1% and its morbidity was 7.6%. With a median follow-up of 33 months, the 5-year DFS/DSS were 43%/49% for patients with positive SN and 83.5%/87.4% for patients with negative SN, respectively. The false-negative rate of SNB was 8.6% and sensitivity 91.4%. On multivariate analysis, DFS was significantly worsened by Breslow thickness (RR=5.6, p<0.001), positive SN (RR=5.0, p<0.001) and male sex (RR=2.9, p=0.001). The presence of a metastatic SN (RR=8.4, p<0.001), male sex (RR=6.1, p<0.001), Breslow thickness (RR=3.2, p=0.013) and ulceration (RR=2.6, p=0.015) were significantly associated with a poorer DSS. CONCLUSION: SNB is a reliable procedure with high sensitivity (91.4%) and low morbidity. Breslow thickness was the only statistically significant parameter predictive of SN status. DFS was worsened in decreasing order by Breslow thickness, metastatic SN and male gender. Similarly DSS was significantly worsened by a metastatic SN, male gender, Breslow thickness and ulceration. These data reinforce the SN status as a powerful staging procedure

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

Anti-tumor necrosis factor drug survival in axial spondyloarthritis is independent of the classification criteria.

To compare the impact of meeting specific classification criteria [modified New York (mNY), European Spondyloarthropathy Study Group (ESSG), and Assessment of SpondyloArthritis international Society (ASAS) criteria] on anti-tumor necrosis factor (anti-TNF) drug retention, and to determine predictive factors of better drug survival. All patients fulfilling the ESSG criteria for axial spondyloarthritis (SpA) with available data on the axial ASAS and mNY criteria, and who had received at least one anti-TNF treatment were retrospectively retrieved in a single academic institution in Switzerland. Drug retention was computed using survival analysis (Kaplan-Meier), adjusted for potential confounders. Of the 137 patients classified as having axial SpA using the ESSG criteria, 112 also met the ASAS axial SpA criteria, and 77 fulfilled the mNY criteria. Drug retention rates at 12 and 24 months for the first biologic therapy were not significantly different between the diagnostic groups. Only the small ASAS non-classified axial SpA group (25 patients) showed a nonsignificant trend toward shorter drug survival. Elevated CRP level, but not the presence of bone marrow edema on magnetic resonance imaging (MRI) scans, was associated with significantly better drug retention (OR 7.9, ICR 4-14). In this cohort, anti-TNF drug survival was independent of the classification criteria. Elevated CRP level, but not positive MRI, was associated with better drug retention.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.