Yi Ching Hsieh

Predictive modeling for the presence of prostate carcinoma using clinical, laboratory, and ultrasound parameters in patients with prostate-specific antigen levels ≤ 10 ng/ml

The objective of the current study was to develop a model for predicting the presence of prostate carcinoma using clinical, laboratory, and transrectal ultrasound (TRUS) data.

Improved detection of prostate cancer using classification and regression tree analysis

PURPOSE To build a decision tree for patients suspected of having prostate cancer using classification and regression tree (CART) analysis. PATIENTS AND METHODS Data were uniformly collected on 1,433 referred men with a serum prostate-specific antigen (PSA) levels of < or = 10 ng/mL who underwent a prostate biopsy. Factors analyzed included demographic, laboratory, and ultrasound data (ie, hypoechoic lesions and PSA density [PSAD]). Twenty percent of the data was randomly selected and reserved for study validation. CART analysis was performed in two steps, initially using PSA and digital rectal examination (DRE) alone and subsequently using the remaining variables. RESULTS CART analysis selected a PSA cutoff of more than 1.55 ng/mL for further work-up, regardless of DRE findings. CART then selected the following subgroups at risk for a positive biopsy: (1) PSAD more than 0.165 ng/mL/cc; (2) PSAD < or = 0.165 ng/mL/cc and a hypoechoic lesion; (3) PSAD < or = 0.165 ng/mL/cc, no hypoechoic lesions, age older than 55.5 years, and prostate volume < or = 44.0 cc; and (4) PSAD < or = 0.165 ng/mL/cc, no hypoechoic lesions, age older than 55.5 years, and 50.25 cc less than prostate volume < or = 80.8 cc. In the validation data set, specificity and sensitivity were 31.3% and 96.6%, respectively. Cancers that were missed by the CART were Gleason score 6 or less in 93.4% of cases. Receiver operator characteristic curve analysis showed that CART and logistic regression models had similar accuracy (area under the curve = 0.74 v 0.72, respectively). CONCLUSION Application of CART analysis to the prostate biopsy decision results in a significant reduction in unnecessary biopsies while retaining a high degree of sensitivity when compared with the standard of performing a biopsy of all patients with an abnormal PSA or DRE.

Delayed therapy with curative intent in a contemporary prostate cancer watchful-waiting cohort

To identify predictors of delayed therapy with curative intent, an increasingly common option in contemporary patients with prostate cancer who initially choose watchful waiting.

GABAergic System Gene Expression Predicts Clinical Outcome in Patients With Neuroblastoma

PURPOSE Neuroblastoma (NB) is a common childhood malignancy characterized by heterogeneous clinical behavior. The purpose of this study was to identify potential NB biomarkers that may improve outcome prediction. PATIENTS AND METHODS The suppression subtractive hybridization (SSH) technique was used to identify the genes differentially expressed between NB and control tissue. RNA isolated from 235 primary NB tumor samples obtained from the Childrens Cancer Group was evaluated for expression of the candidate markers using quantitative reverse transcriptase polymerase chain reaction (Taqman assays). The association between the mRNA expression levels in the identified candidate genes and clinical outcome was evaluated. RESULTS SSH analysis identified differential expression of members of the GABAergic gene family in NB. Lower levels of gamma-aminobutyric acid (GABA) receptor-associated protein (GABARAP) gene expression predict decreased survival among all patients. GABA(A) delta receptor subunit gene expression was predictive of a poor outcome among Evans stage IV-S patients. An index of five coexpressed GABA(A) receptor subunits was identified (GABA(A) profile [GAP score]). Patients with a higher GAP score (> -1) had a survival advantage. Multivariate analysis showed that GABARAP and GABA(A) alpha2 receptor subunit gene expression levels and GAP score remained predictors of clinical outcome after accounting for current prognostic indicators. CONCLUSION Dysregulation of the GABAergic system may constitute a fundamental event in the development of NB, and assessment of GABAergic system gene expression could provide improved patient stratification and potential new therapies.

Classification and regression tree analysis for the prediction of aggressive prostate cancer on biopsy

PURPOSE Prostate cancer screening allows early cancer detection but not all patients benefit from subsequent therapy. Thus, identifying patients who are likely to harbor aggressive cancer could significantly decrease the number of prostate biopsies performed. MATERIALS AND METHODS Data were collected on 1,563 consecutive referred men with serum PSA 10 ng/ml or less who underwent an initial prostate biopsy. Predictors of aggressive cancer (Gleason sum 7 or greater) were identified using CART analysis. Model building was done in a randomly selected training set (70% of the data) and validation was completed using the remaining data. RESULTS Cancer was detected in 406 men (26.1%). Gleason 7 or greater cancer was found in 130 men (8.3%). CART created a decision tree that identified certain groups at risk for aggressive cancer, namely 1) PSAD greater than 0.165 ng/ml/cc, and 2) PSAD greater than 0.058 to 0.165 ng/ml/cc or less, age greater than 57.5 years and prostate volume greater than 22.7 cc. The incidence of aggressive prostate cancer was 1.1% when PSAD was 0.058 ng/ml/cc or less in the validation set. The sensitivity and specificity of CART for identifying men with aggressive cancer were 100% and 31.8% for model building data, and 91.5% and 33.5% for the validation data set, respectively. CONCLUSIONS CART identified groups at risk for aggressive prostate cancer. Application of this CART could decrease unnecessary biopsies by 33.5% when only a diagnosis of high grade prostate cancer would lead to subsequent therapy.

Predictors of Delayed Therapy after Expectant Management for Localized Prostate Cancer in the Era of Prostate-Specific Antigen

Objective: To identify risk factors for delayed cancer-directed intervention in modern era prostate cancer patients who initially elect expectant management. Materials and Methods: An observational, cohort study of expectantly managed patients, diagnosed with clinical T1–4NxM₀ prostate cancer between 1993 and 2000 was carried out. Data including TNM stage, age, serum prostate-specific antigen (PSA), prostate gland volume by transrectal ultrasound, Gleason score, percent biopsies positive for cancer, imaging results, initial treatment selection, and outcome data were collected on all patients. Results: 192 of 561 patients (34.3%) elected expectant management, and follow-up data were available for 187 (97.4%) patients. With a median follow-up of 3.6 years, 90 (48.1%) patients had a cancer-directed intervention. Gleason score (p = 0.0097) and percent of positive biopsy cores (p = 0.03) were independent predictors of time to intervention. As expected, PSA doubling time became the most significant predictor of intervention (p = 0.0057) when added to the model. These independent covariates are able to characterize low-, intermediate- and high-risk groups for cancer-directed intervention. Conclusions: Cancer-directed intervention is common in patients who choose expectant management in the PSA era. Gleason score and percent of positive biopsy cores predict cancer-directed interventions, thus, these patients may be least suitable for expectant management.