Integrating additional factors into the TNM staging for cutaneous melanoma by machine learning.

BACKGROUND: Integrating additional factors into the TNM staging system is needed for more accurate risk classification and survival prediction for patients with cutaneous melanoma. In the present study, we introduce machine learning as a novel tool that incorporates additional prognostic factors to improve the current TNM staging system. METHODS AND FINDINGS: Cancer-specific survival data for cutaneous melanoma with at least a 5 years follow-up were extracted from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute and split into the training set (40,781 cases) and validation set (5,390 cases). Five factors were studied: the primary tumor (T), regional lymph nodes (N), distant metastasis (M), age (A), and sex (S). The Ensemble Algorithm for Clustering Cancer Data (EACCD) was applied to the training set to generate prognostic groups. Utilizing only T, N, and M, a basic prognostic system was built where patients were stratified into 10 prognostic groups with well-separated survival curves, similar to 10 AJCC stages. These 10 groups had a significantly higher accuracy in survival prediction than 10 stages (C-index = 0.7682 vs 0.7643; increase in C-index = 0.0039, 95% CI = (0.0032, 0.0047); p-value = 7.2×10-23). Nevertheless, a positive association remained between the EACCD grouping and the AJCC staging (Spearman's rank correlation coefficient = 0.8316; p-value = 4.5×10-13). With additional information from A and S, a more advanced prognostic system was established using the training data that stratified patients into 10 groups and further improved the prediction accuracy (C-index = 0.7865 vs 0.7643; increase in C-index = 0.0222, 95% CI = (0.0191, 0.0254); p-value = 8.8×10-43). Both internal validation using the training set and temporal validation using the validation set showed good stratification and a high predictive accuracy of the prognostic systems. CONCLUSIONS: The EACCD allows additional factors to be integrated into the TNM to create a prognostic system that improves patient stratification and survival prediction for cutaneous melanoma. This integration separates favorable from unfavorable clinical outcomes for patients and improves both cohort selection for clinical trials and treatment management.

A prognostic system for epithelial ovarian carcinomas using machine learning.

INTRODUCTION: Integrating additional factors into the International Federation of Gynecology and Obstetrics (FIGO) staging system is needed for accurate patient classification and survival prediction. In this study, we tested machine learning as a novel tool for incorporating additional prognostic parameters into the conventional FIGO staging system for stratifying patients with epithelial ovarian carcinomas and evaluating their survival. MATERIAL AND METHODS: Cancer-specific survival data for epithelial ovarian carcinomas were extracted from the Surveillance, Epidemiology, and End Results (SEER) program. Two datasets were constructed based upon the year of diagnosis. Dataset 1 (39 514 cases) was limited to primary tumor (T), regional lymph nodes (N) and distant metastasis (M). Dataset 2 (25 291 cases) included additional parameters of age at diagnosis (A) and histologic type and grade (H). The Ensemble Algorithm for Clustering Cancer Data (EACCD) was applied to generate prognostic groups with depiction in dendrograms. C-indices provided dendrogram cutoffs and comparisons of prediction accuracy. RESULTS: Dataset 1 was stratified into nine epithelial ovarian carcinoma prognostic groups, contrasting with 10 groups from FIGO methodology. The EACCD grouping had a slightly higher accuracy in survival prediction than FIGO staging (C-index = 0.7391 vs 0.7371, increase in C-index = 0.0020, 95% confidence interval [CI] 0.0012-0.0027, p = 1.8 × 10-7 ). Nevertheless, there remained a strong inter-system association between EACCD and FIGO (rank correlation = 0.9480, p = 6.1 × 10-15 ). Analysis of Dataset 2 demonstrated that A and H could be smoothly integrated with the T, N and M criteria. Survival data were stratified into nine prognostic groups with an even higher prediction accuracy (C-index = 0.7605) than when using only T, N and M. CONCLUSIONS: EACCD was successfully applied to integrate A and H with T, N and M for stratification and survival prediction of epithelial ovarian carcinoma patients. Additional factors could be advantageously incorporated to test the prognostic impact of emerging diagnostic or therapeutic advances.

Clinical Readiness Program: Refocusing the Military Health System.

INTRODUCTION: The Military Health System serves to globally provide health services and trained medical forces. Military providers possess variable levels of deployment preparedness. The aim of the Clinical Readiness Program is to develop and assess the knowledge, skills, and abilities (KSAs) needed for combat casualty care. METHODS: The Clinical Readiness Program developed a KSA metric for general and orthopedic surgery. The KSA methodology underwent a proof of concept in six medical treatment facilities. RESULTS: The KSA metric feasibly quantifies the combat relevance of surgical practice. Orthopedic surgeons are more likely than general surgeons to meet the threshold. Medical treatment facilities do not provide enough demand for general surgery services to achieve readiness. CONCLUSION: The Clinical Readiness Program identifies imbalances between the health care delivery and readiness missions. To close the readiness gap, the Military Health System needs to recapture high KSA value procedures, expand access to care, and/or partner with civilian institutions.

Evaluation of Surgical Disparities Between African American and European American Women Treated for Breast Cancer Within an Equal-Access Military Hospital.

BACKGROUND: Survival disparities between African American women (AAW) and European American women (EAW) with invasive breast cancer may be attributable, in part, to access to or quality of medical care. In this study, we evaluated surgical disparities between AAW and EAW treated within an equal-access military treatment facility (MTF). METHODS: All AAW (N = 271) and EAW (N = 628) with Stage I-III breast cancer who had their initial diagnosis performed at Murtha Cancer Center at Walter Reed National Military Medical Center were identified. Differences in surgical interval (time between diagnosis and definitive breast surgery) and surgical procedures were evaluated using χ2 and Student t-tests while survival was analyzed using Kaplan-Meier survival estimates and log-rank tests. A P value < 0.05 was used to define significance. RESULTS: Surgical intervals did not differ significantly between populations with an average of 36.3 days in AAW and 33.9 days in EAW. Frequency of the percentage of women undergoing reexcision, mastectomy, and prophylactic removal of the contralateral breast did not differ significantly between populations. Likewise, frequency of sentinel lymph node biopsy and 5-year survival were not significantly different between AAW compared to EAW. DISCUSSION: Surgical intervals and procedures were similar between AAW and EAW treated within an equal-access MTF. These data demonstrate that the availability of quality surgical care to all patients with stage I-III breast cancer may eliminate survival disparities between AAW and EAW, emphasizing the importance of equalizing access to breast care.

Creating Prognostic Systems for Well-Differentiated Thyroid Cancer Using Machine Learning.

Updates to staging models are needed to reflect a greater understanding of tumor behavior and clinical outcomes for well-differentiated thyroid carcinomas. We used a machine learning algorithm and disease-specific survival data of differentiated thyroid carcinoma from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute to integrate clinical factors to improve prognostic accuracy. The concordance statistic (C-index) was used to cut dendrograms resulting from the learning process to generate prognostic groups. We created one computational prognostic model (7 prognostic groups with C-index = 0.8583) based on tumor size (T), regional lymph nodes (N), status of distant metastasis (M), and age to mirror the contemporary American Joint Committee on Cancer (AJCC) staging system (C-index = 0.8387). We showed that adding histologic type (papillary and follicular) improved the survival prediction of the model. We also showed that 55 is the best cutoff of age in the model, consistent with the changes from the most recent 8th edition staging manual from AJCC. The demonstrated approach has the potential to create prognostic systems permitting data driven and real time analysis that can aid decision-making in patient management and prognostication.

Comparative Survival Analysis of Invasive Breast Cancer Patients Treated by a U.S. Military Medical Center and Matched Patients From the U.S. General Population.

OBJECTIVE: Many differences between U.S. military beneficiaries and the U.S. general population, including differences in health care access, are known factors affecting invasive breast cancer outcomes. Thus, comparing the two populations for any outcome differences and their contributing factors may provide insights to breast cancer prognosis. METHODS: Using a marginal Cox proportional hazards regression model, we compared disease-specific survival (DSS) and 5-year DSS rates between 418 patients from the Clinical Breast Care Project at the Walter Reed National Military Medical Center (CBCP-WR) and a set of 1:5 randomly matched patients from the Surveillance, Epidemiology, and End Results program. Patients were compared in the "demographic model" (adjusted by diagnosis year, age, and race) and the "overall model" (further adjusted by estrogen receptor, progesterone receptor, stage, and grade). RESULTS: In the "overall model," CBCP-WR patients were less likely overall to die from breast cancer (hazard ratio [HR] = 0.631, 95% confidence interval [CI] = 0.437-0.911; p = 0.014). This increase in survival was also significant in African American patients (HR = 0.524, 95% CI = 0.277-0.992; p = 0.047) and patients older than 50 (HR = 0.511, 95% CI = 0.306-0.854; p = 0.010). The advantage in 5-year DSS rate for CBCP-WR patients was 5.3% (93.1% vs. 87.8%; p < 0.001) in the "demographic model" and 3.4% (91.3% vs. 87.9%; p = 0.018) in the "overall model." CONCLUSION: CBCP-WR patients demonstrated significantly better DSS over matched SEER patients. Although a portion of the outcome disparity, i.e., 36% of the 5.3% DSS rate difference, could be explained by differences in tumor characteristics, the cause(s) behind the majority of the disparity has yet to be identified. Identification and further analysis of contributing factors to survival differences have the potential to improve clinical practice and outcomes for invasive breast cancer patients.

The anatomy of the TNM for colon cancer.

BACKGROUND: To visualize the anatomy as revealed by dendrograms of the tumor, lymph node, and metastasis (TNM) staging system for colon cancer and compare it with the Dukes' system. METHODS: A hierarchical clustering algorithm generated tree-structured dendrograms that stratified patients according to survival only. The dendrograms were constructed with the same prognostic variables used for the TNM. Because combinations of prognostic factors were stratified only on survival, additional factors of any number and type could be integrated into the TNM without changing the TNM categories. RESULTS: The algorithm provided a step-by-step visualization of the TNM and the Dukes' system for colon cancer. Dendrograms and associated 5-year survival rates were generated for the T category only, the N category only, the T, N combination, and combinations of the T, N, and M, and the T, N, M with histological grade. Dendrograms revealed visual differences between the structure of TNM and the Dukes' system of staging. Dendrograms also revealed how variations in prognostic factors changed survival. By cutting dendrograms along their dissimilarity axis, multiple prognostic subgroups could be created for colon cancer that may reflect outcomes that are more accurate to estimate. CONCLUSIONS: Dendrograms provide a new way to view cancer patient staging. They reveal a visual step-by-step hierarchical relationship between survival rates and combinations of prognostic variables. The dendrograms also revealed fundamental differences between the TNM and the Dukes system of staging. By stratifying on survival only, additional factors including molecular factors can be added to the TNM, because it classifies patients according to survival rates only and not according to pre-set rules of prognostic factors and stage groups. The clinical implications of stratifying only survival are discussed.

Nonsteroidal anti-inflammatory drugs may affect cytokine response and benefit healing of combat-related extremity wounds.

BACKGROUND: After adequate operative debridement and antimicrobial therapies, combat-related extremity wounds that either heal or fail are both associated with a distinct inflammatory response. Short-term use of nonsteroidal anti-inflammatory drugs in postoperative pain management may affect this response and, by consequence, the healing potential of these wounds. We investigated whether patients treated with nonsteroidal anti-inflammatory drugs had a distinct inflammatory response; different rates of critical colonization, defined as >105 colony forming units on quantitative bacteriology; and healing potential. METHODS: We retrospectively reviewed the records of 73 patients with combat-related extremity wounds. Patients were separated into 2 groups: those who received nonsteroidal anti-inflammatory drugs during the debridement period (nonsteroidal anti-inflammatory drugs group, N = 17) and those who did not (control group; N = 56). Serum and wound tissue samples collected during each operative debridement were measured for 32 known cytokines and tested for quantitative bacteriology, respectively. We compared cytokine concentrations between groups and then designed a logistic regression model to identify variables associated with successful wound healing, while controlling for known confounders. RESULTS: Despite similar demographics and wound characteristics, the nonsteroidal anti-inflammatory drugs group had significant lesser concentrations of inflammatory cytokines, interleukin-2, interleukin-6, interleukin-8, and monocyte chemoattractant protein-1. On multivariate analysis, nonsteroidal anti-inflammatory drug treatment emerged as a predictor of successful wound healing after controlling for known confounders such as wound size, tobacco use, Acute Physiology and Chronic Health Evaluation II score, and critical colonization. CONCLUSION: Treatment with nonsteroidal anti-inflammatory drugs for postoperative pain management after major combat-related extremity trauma is associated with lesser concentrations of inflammatory cytokines and may contribute to a more favorable inflammatory response leading to successful wound healing.

An Algorithm for Creating Prognostic Systems for Cancer.

The TNM staging system is universally used for classification of cancer. This system is limited since it uses only three factors (tumor size, extent of spread to lymph nodes, and status of distant metastasis) to generate stage groups. To provide a more accurate description of cancer and thus better patient care, additional factors or variables should be used to classify cancer. In this paper we propose a hierarchical clustering algorithm to develop prognostic systems that classify cancer according to multiple prognostic factors. This algorithm has many potential applications in augmenting the data currently obtained in a staging system by allowing more prognostic factors to be incorporated. The algorithm clusters combinations of prognostic factors that are formed using categories of factors. The dissimilarity between two combinations is determined by the area between two corresponding survival curves. Groups from cutting the dendrogram and survival curves of the individual groups define our prognostic systems that classify patients using survival outcomes. A demonstration of the proposed algorithm is given for patients with breast cancer from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute.

An algorithm for expanding the TNM staging system.

AIM: We describe a new method to expand the tumor, lymph node, metastasis (TNM) staging system using a clustering algorithm. Cases of breast cancer were used for demonstration. MATERIALS & METHODS: An unsupervised ensemble-learning algorithm was used to create dendrograms. Cutting the dendrograms produced prognostic systems. RESULTS: Prognostic systems contained groups of patients with similar outcomes. The prognostic systems based on tumor size and lymph node status recapitulated the general structure of the TNM for breast cancer. The prognostic systems based on tumor size, lymph node status, histologic grade and estrogen receptor status revealed a more detailed stratification of patients when grade and estrogen receptor status were added. CONCLUSION: Prognostic systems from cutting the dendrogram have the potential to improve and expand the TNM.

Tumour location within the breast: Does tumour site have prognostic ability?

INTRODUCTION: Tumour location within the breast varies with the highest frequency in the upper outer quadrant (UOQ) and lowest frequency in the lower inner quadrant (LIQ). Whether tumour location is prognostic is unclear. To determine whether tumour location is prognostic, associations between tumour site and clinicopathological characteristics were evaluated. MATERIALS AND METHODS: All patients enrolled in the Clinical Breast Care Project whose tumour site-UOQ, upper inner quadrant (UIQ), central, LIQ, lower outer quadrant (LOQ)-was determined by a single, dedicated breast pathologist were included in this study. Patients with multicentric disease (n = 122) or tumours spanning multiple quadrants (n = 381) were excluded from further analysis. Clinicopathological characteristics were analysed using chi-square tests for univariate analysis with multivariate analysis performed using principal components analysis (PCA) and multiple logistic regression. Significance was defined as P < 0.05. RESULTS: Of the 980 patients with defined tumour location, 30 had bilateral disease. Tumour location in the UOQ (51.5%) was significantly higher than in the UIQ (15.6%), LOQ (14.2%), central (10.6%), or LIQ (8.1%). Tumours in the central quadrant were significantly more likely to have higher tumour stage (P = 0.003) and size (P < 0.001), metastatic lymph nodes (P < 0.001), and mortality (P = 0.011). After multivariate analysis, only tumour size and lymph node status remained significantly associated with survival. CONCLUSIONS: Evaluation of tumour location as a prognostic factor revealed that although tumours in the central region are associated with less favourable outcome, these associations are not independent of location but rather driven by larger tumour size. Tumours in the central region are more difficult to detect mammographically, resulting in larger tumour size at diagnosis and thus less favourable prognosis. Together, these data demonstrate that tumour location is not an independent prognostic factor.

Molecular signatures of lymph node status by intrinsic subtype: gene expression analysis of primary breast tumors from patients with and without metastatic lymph nodes.

BACKGROUND: Identification of a gene expression signature in primary breast tumors that could classify patients by lymph node status would allow patients to avoid the morbidities of surgical disruption of the lymph nodes. Attempts to identify such a signature have, to date, been unsuccessful. Because breast tumor subtypes have unique molecular characteristics and different sites of metastasis, molecular signatures for lymph node involvement may vary by subtype. METHODS: Gene expression data was generated from HG U133A 2.0 arrays for 135 node positive and 210 node negative primary breast tumors. Intrinsic subtype was assigned using the BreastPRS. Differential gene expression analysis was performed using one-way ANOVA using lymph node status as the variable with a False-discovery rate <0.05, to define significance. RESULTS: Luminal A tumors were most common (51%) followed by basal-like (27%), HER2-enriched (14%) luminal B (7%) and normal-like (1%). Basal-like and luminal A tumors were less likely to have metastatic lymph nodes (35% and 37%, respectively) compared to luminal B or HER2-enriched (52% and 51%, respectively). No differentially expressed genes associated with lymph node status were detected when all tumors were considered together or within each subtype. CONCLUSIONS: Gene expression patterns from the primary tumor are not able to stratify patients by lymph node status. Although the primary breast tumor may influence tumor cell dissemination, once metastatic cells enter the lymphatics, it is likely that characteristics of the lymph node microenvironment, such as establishment of a pre-metastatic niche and release of pro-survival factors, determine which cells are able to colonize. The inability to utilize molecular profiles from the primary tumor to determine lymph node status suggest that other avenues of investigation, such as how systemic factors including diminished immune response or genetic susceptibility contribute to metastasis, may be critical in the development of tools for non-surgical assessment of lymph node status with a corresponding reduction in downstream sequelae associated with disruption of the lymphatics.

Circulating regulatory T cells (CD4+CD25+FOXP3+) decrease in breast cancer patients after vaccination with a modified MHC class II HER2/neu (AE37) peptide.

Regulatory T cells (T(Reg)), CD4(+)CD25(+)FOXP3(+), are implicated in suppressing tumor immune responses. We analyzed peripheral blood lymphocytes (PBL) from breast cancer patients receiving a modified HLA class II HER2/neu peptide (AE37) vaccine for T(Reg) cells and correlated their levels with vaccine-specific immune responses. The mean CD4(+)CD25(+)FOXP3(+) T(Reg) cells decreased in patients with vaccination with no significant difference in serum TGF-ß levels. IFN-γ ELISPOT and DTH increased after vaccination with a good correlation between T(Reg) cell reduction and size of DTH to AE37. The T(Reg) cell reduction and associated immune response suggest that AE37 may be clinically useful.

Clinical and immunologic responses of HLA-A3+ breast cancer patients vaccinated with the HER2/neu-derived peptide vaccine, E75, in a phase I/II clinical trial.

BACKGROUND: We have treated disease-free breast cancer patients with an HER2/neu-derived peptide, E75, as an adjuvant vaccine. E75 was originally described as HLA-A2-restricted and has been previously tested in this population. Based on computer modeling, E75 is predicted to bind to HLA-A3, and preclinical data support this. We conducted a clinical trial of E75 in HLA-A3(+), A2(-) (A3) patients. STUDY DESIGN: Disease-free breast cancer patients were enrolled after standard therapy in phase I/II trials. A3 patients were enrolled in parallel with A2 patients and vaccinated with E75 and granulocyte-macrophage colony-stimulating factor immunoadjuvant. A2(-), A3(-) patients were followed as controls. Toxicities were graded. Immunologic responses were assessed by delayed-type hypersensitivity reactions and E75-specific interferon-gamma enzyme-linked immunosorbent spot assay. Clinical recurrences were documented. RESULTS: Thirteen A3 patients completed the vaccine schedule. Clinicopathologic features were similar between A3, A2, and control patients, except for more HER2/neu-overexpressing tumors in the A2 group and more estrogen-receptor/progesterone-receptor-negative tumors in A2 and A3 groups. Toxicity profiles and postvaccination delayed-type hypersensitivity were similar in A3 and A2 patients. Enzyme-linked immunosorbent spot assay results varied, but A3 patients' median spots increased pre- to postvaccination (p = 0.2). Recurrences were lower in the A3 group (7.7%) at 30-month median follow-up compared with published recurrence in A2-vaccinated (8.3%) and control groups (14.8%) at 26-month median follow-up. CONCLUSIONS: HLA restriction limits potential use of peptide-based cancer vaccines. This trial demonstrates that HLA-A3 patients respond similarly to E75 vaccination as HLA-A2 patients, suggesting the potential use of the E75 vaccine in up to 76% of the population.

Evolving treatment strategies for gallbladder cancer.

Gallbladder cancer is an uncommon cancer that has traditionally been associated with a poor prognosis. In the era of laparoscopic cholecystectomy, incidental gallbladder cancer has dramatically increased and now constitutes the major way patients present with gallbladder cancer. While patients with incidental gallbladder cancer have a better survival than patients with nonincidental gallbladder cancer, incidental gallbladder cancer can be associated with a varied prognosis. Imaging with computed tomography (CT), magnetic resonance imaging (MRI), and [18]F-fluorodeoxyglucose (FDG) positron emission tomography (PET), as well as diagnostic laparoscopy, all have varying roles in the workup of patients with incidental gallbladder cancer. For patients with T1b, T2, and T3 incidental gallbladder cancer re-resection is generally recommended. At re-exploration, many patients with incidental gallbladder cancer will have residual disease. Definitive oncologic management requires re-resection of the liver, portal lymphadenectomy, and attention to the common bile duct. The extent of the hepatic resection should be dictated by the ability to achieve a microscopically negative (R0) margin. Routine resection of the common bile duct is unnecessary but should be undertaken in the setting of a positive cystic duct margin. If an incidental gallbladder cancer is discovered at the time of surgery, whether the surgeon should directly proceed with a more definitive oncologic operation should depend on the surgeon's skill-set and experience. Gallbladder cancer has a propensity to recur. Although data for adjuvant therapy following resection are limited, some data do suggest a survival benefit for adjuvant chemoradiation therapy. Management of patients with gallbladder cancer requires a multidisciplinary approach with input from a surgeon skilled in hepatobiliary surgery.

The impact of HER2/neu expression level on response to the E75 vaccine: from U.S. Military Cancer Institute Clinical Trials Group Study I-01 and I-02.

PURPOSE: HER2/neu, a source of immunogenic peptides, is expressed in >75% of breast cancer patients. We have conducted clinical trials with the HER2/neu E75 peptide vaccine in breast cancer patients with varying levels of HER2/neu expression. Vaccine response based on HER2/neu expression level was analyzed. EXPERIMENTAL DESIGN: Patients were stratified by HER2/neu expression. Low expressors (n = 100) were defined as HER2/neu immunohistochemistry (IHC) 1(+) to 2(+) or fluorescence in situ hybridization < 2.0. Overexpressors (n = 51) were defined as IHC 3(+) or fluorescence in situ hybridization > or = 2.0. Additional analyses were done stratifying by IHC status (0-3(+)). Standard clinocopathlogic factors, immunologic response (in vivo delayed-type hypersensitivity reactions; ex vivo human leukocyte antigen A2:immunoglobulin G dimer assay), and clinical responses (recurrence; mortality) were assessed. RESULTS: Low-expressor (control, 44; vaccinated, 56) versus overexpressor patients (control, 22; vaccinated, 29) were assessed. Low expressors, overexpressors, and most IHC-status vaccinated groups responded immunologically. Vaccinated low-expressor patients had larger maximum immunologic responses compared with overexpressor patients (P = 0.04), and vaccinated IHC 1(+) patients had increased long-term immune response (P = 0.08). More importantly, compared with controls, low-expressor patients had a mortality reduction (P = 0.08). The largest decrease in mortality was seen in IHC 1(+) patients (P = 0.05). In addition, a subset of overexpressor patients (n = 7) received trastuzumab before vaccination, and this combination seems safe and immunologically beneficial. CONCLUSIONS: Most patients with various levels of HER2/neu expression responded immunologically and seemed to benefit from vaccination. The low expressors, specifically IHC 1(+) patients, had more robust immunologic responses and may derive the greatest clinical benefit from the E75 vaccine.

Longterm followup assessment of a HER2/neu peptide (E75) vaccine for prevention of recurrence in high-risk prostate cancer patients.

BACKGROUND: E75 is an immunogenic peptide from the HER2/neu protein that is expressed in prostate cancer. High-risk prostate cancer (HRPC) patients demonstrating varying levels of HER2/neu expression were vaccinated with E75 peptide plus granulocyte-macrophage colony-stimulating factor to prevent postprostatectomy PSA and clinical recurrences. STUDY DESIGN: Forty evaluable HRPC patients were prospectively identified using the validated Center for Prostate Disease Research/CaPSURE high-risk equation and enrolled. HLA-A2(+) patients (n = 21) were vaccinated, and HLA-A2(-) patients (n = 19) were followed as clinical controls. All patients were assessed for clinicopathologic factors, biochemical recurrence (consecutive PSA value >or= 0.2 ng/mL), clinical recurrence, and survival. RESULTS: Comparing the vaccinated and control groups, there were no statistical differences in clinicopathologic prognostic factors. At a median followup of 58.2 months (range 18.8 to 62.7 months), PSA recurrence rates were not different between vaccinated (29%) and control (26%) groups. Median time to recurrence from operation was 14.0 months (range 5.7 to 53.4 months) versus 8.5 months (range 4.7 to 34.1 months) (p = 0.7), respectively. Three vaccinated patients had PSA recurrences during the vaccine series. If these patients were excluded, median time to recurrence for the vaccinated group extends to 42.7 months (range 20.4 to 53.4 months) (p = 0.4). Study-wide, only one clinical recurrence and death occurred in a vaccinated patient that was early in the vaccine series. Subset analysis comparing vaccinated recurrent patients with control recurrences noted some statistical trends. CONCLUSIONS: The HER2/neu (E75) vaccine can prevent or delay recurrences in HRPC patients if completed before PSA recurrence. A larger randomized phase II trial in HLA-A2(+) patients will be required to confirm these findings.

Sentinel lymph node biopsy in melanoma.

Sentinel lymph node biopsy (SLNB) for patients with newly diagnosed localized invasive melanoma provides excellent prognostic information and results in improved regional disease control. Prior to the common use of SLNB, regional nodal recurrence was the single most common site of melanoma recurrence, with symptomatic, bulky disease that could be disabling and difficult or impossible to control. With the widespread use of SLNB, regional recurrence of melanoma is much less frequent. Even without clear evidence of improvement in overall survival, the significant and reliable prognostic information and the improved regional control make sentinel node biopsy an important procedure that should be offered routinely to many patients with newly diagnosed melanoma.

Optimal dose and schedule of an HER-2/neu (E75) peptide vaccine to prevent breast cancer recurrence: from US Military Cancer Institute Clinical Trials Group Study I-01 and I-02.

BACKGROUND: E75, a HER-2/neu-derived peptide, was administered as a preventive vaccine with granulocyte-macrophage-colony-stimulating factor (GM-CSF) in disease-free lymph node-positive (NP) and lymph node-negative (NN) breast cancer (BCa) patients. The optimal biologic dose (OBD) was determined based on toxicity and immunologic response. METHODS: Patients were vaccinated over 6 months (3, 4, or 6 times) with different doses of E75 plus GM-CSF. Toxicities were graded per National Cancer Institute Common Terminology Criteria. GM-CSF was reduced for significant toxicity. Immunologic response was measured by delayed type hypersensitivity test (DTH), and E75-specific CD8+ T-cells were quantified with human leukocyte antigen-A2:immunoglobulin G dimer and flow cytometry. RESULTS: Ninety-nine patients (48 NP and 51 NN) were vaccinated in 7 dose groups. The OBD was 1000 microg E75 plus 250 microg GM-CSF monthly x 6. The optimal dose group (ODG, n = 29) experienced similar toxicities to the suboptimal dose group (SDG, n = 70), which was comprised of the remaining 6 groups. The ODG demonstrated a trend toward an increase in the average postvaccine dimer (0.87 +/- 0.10% vs 0.67 +/- 0.05%; P = .07), a significantly larger DTH response (21.5 +/- 2.5 mm vs 11.3 +/- 1.3 mm; P = .0002), and a trend toward decreased recurrences (3.4% vs 12.9%; P = .27). Compared with the SDG, the ODG had larger tumors (percentage > or =T2: 55% vs 23%; P = .004), more positive lymph nodes (percentage NP: 76% vs 37%; P = .001), and higher grade tumors (percentage grade 3: 52% vs 30%; P = .07), but a shorter median follow-up time (20 months vs 32 months; P < .001). CONCLUSIONS: Compared with suboptimally dosed patients, the optimally dosed E75 vaccine in disease-free BCa patients had similar toxicity but enhanced HER-2/neu-specific immunity that may lead to decreased recurrences with additional follow-up.