Validation study of the accuracy of a postoperative nomogram for recurrence after radical prostatectomy for localized prostate cancer

Preoperative PSMA-PET/CT as a predictor of biochemical persistence and early recurrence following radical prostatectomy with lymph node dissection

BACKGROUND

This study aims to evaluate the predictive value of lymph nodes (LN) suspicious for metastases on preoperative prostate-specific membrane antigen (PSMA) PET/CT for biochemical persistence (BCP) and early biochemical recurrence (BCR) following robotic-assisted radical prostatectomy (RARP) with extended pelvic LN dissection (ePLND).

METHODS

We evaluated 213 patients with intermediate and high-risk prostate cancer (PCa) who underwent clinical staging with preoperative ⁶⁸Ga- or ¹⁸F-PSMA-PET/CT scan and subsequent RARP with ePLND. Patients were grouped as PSMA- or PSMA+ depending on their LN status on PSMA-PET/CT and subdivided according to histological LN status in pN0 or pN1. Diagnostic accuracy of PSMA-PET/CT for the detection of pN1 was evaluated. BCP was defined as a first postoperative serum PSA level ≥0.1 ng/mL 6-12 weeks following RP. Early BCR was defined as detectable PSA > 0.2 ng/mL within 12 months of follow-up. Univariable logistic regression analyses were used to evaluate the effect of PSMA+ on BCP and BCR.

RESULTS

Forty patients (19%) were PSMA+. The overall incidence of pN1 was 23%. Sensitivity, specificity, PPV and NPV on a per patient level for the detection of pN1 was 29%, 84%, 35%, and 80% respectively. BCP was observed in 26 of 211 patients (12%) and early BCR in 23 of 110 patients (21%). The presence of PSMA+ was a significant predictor for BCP (OR 7.1, 2.9-17.1 95% CI) and BCR (OR 8.1, 2.9-22.6 95% CI).

CONCLUSION

Preoperative PSMA-PET/CT may be a valuable tool for patient counseling for RARP and ePLND as it is a significant predictor for the risk of postoperative BCP and early BCR. We conclude that an ePLND should not be avoided in men with intermediate or high-risk PCa and preoperative negative PSMA-PET/CT, as 20% have microscopic LN metastasis.

Radiotherapy after Prostatectomy

Aims and background

The role of radiotherapy after prostatectomy is controversial. This paper tries to give some guidelines for everyday practice through an analysis of literature data.

Methods

The potential role of radiotherapy in the adjuvant and salvage setting is discussed. We also report and interpret available literature data for both settings.

Results

As regards an increase in or detectable prostate-specific antigen (PSA) after radical prostatectomy, about 40–50% of patients are rendered bNED with local salvage radiotherapy, but only 10–50% are long-term (5 years) biochemically controlled. A timely salvage treatment is crucial to optimize control probability. As regards adjuvant radiotherapy for undetectable postoperative PSA in patients at high risk of failure as judged on pathology, results are more encouraging. Recent data report bNED rates ≥70% at 5 years.

Conclusions

Although results are far from satisfactory, salvage radiotherapy should be considered for every patient with an increased or detectable PSA after surgery. Adjuvant radiotherapy seems preferable to salvage radiotherapy for patients at high (>30%) risk of failure.

Wrong to be Right: Margin Laterality is an Independent Predictor of Biochemical Failure After Radical Prostatectomy

OBJECTIVES

To examine the impact of positive surgical margin (PSM) laterality on failure after radical prostatectomy (RP). A PSM can influence local recurrence and outcomes after salvage radiation. Unlike intrinsic risk factors, a PSM is caused by intervention and thus iatrogenic failures may be elucidated by analyzing margin laterality as surgical approach is itself lateralized.

PATIENTS AND METHODS

We reviewed 226 RP patients between 1991 and 2013 with PSM. Data includes operation type, pre/postoperative PSA, surgical pathology, and margin type (location, focality, laterality). The median follow-up was 47 months. Biochemical recurrence after RP was defined as PSA≥0.1 ng/mL or 2 consecutive rises above nadir. Ninety-two patients received salvage radiation therapy (SRT). Failure after SRT was defined as any PSA≥0.2 ng/mL or greater than presalvage. Kaplan-Meier and Cox multivariate analyses compared relapse rates.

RESULTS

The majority of PSM were iatrogenic (58%). Laterality was associated with differences in median relapse: right 20 versus left 51 versus bilateral 14 months (P<0.01). Preoperative PSA, T-stage, Gleason grade, and laterality were associated with biochemical progression on univariate and multivariate analyses. Right-sided margins were more likely to progress than left (hazard ratio, 1.67; P=0.04). More right-sided margins were referred for SRT (55% right vs. 23% left vs. 22% bilateral), but were equally salvaged. Only T-stage and pre-SRT PSA independently influenced SRT success.

CONCLUSIONS

Most PSM are iatrogenic, with right-sided more likely to progress (and sooner) than left sided. Margin laterality is a heretofore unrecognized independent predictor of biochemical relapse and hints at the need to modify the traditional unilateral surgical technique.

Validation of the Kattan Nomogram for Prostate Cancer Recurrence After Radical Prostatectomy

BACKGROUND

The Kattan postoperative radical prostatectomy (RP) nomogram is used to predict biochemical recurrence-free progression (BCRFP) after RP. However, external validation among contemporary patients using modern outcome definitions is limited.

METHODS

A total of 1,931 patients who underwent RP at Roswell Park Cancer Institute (RPCI) between 1993 and 2014 (median follow-up, 47 months; range, 0-244 months) were assessed for NCCN-defined biochemical failure (BF) and RPCI-defined treatment failure (TF). Actual rates of biochemical failure-free survival (BFS; defined as 1 - BF) and treatment failure-free survival (TFS; defined as 1 - TF) were compared with Kattan BCRFP nomogram predictions.

RESULTS

The Kattan BCRFP nomogram predictions at 5 and 10 years were predictive of BFS (area under the receiver operating characteristic curve [AUC], 0.772) and TFS (AUC, 0.774). The Kattan BCRFP nomogram tended to underestimate BFS and TFS compared with actual outcomes. The Kattan 5-year BCRFP predictions consistently overestimated actual 5-year BFS outcomes among subgroups of high- and intermediate-risk patients with at least 5-year outcomes.

CONCLUSIONS

The Kattan BCRFP nomogram is a robust predictor of NCCN-defined BF in a large sample of patients with RP with substantial follow-up and modern, standardized failure definitions.

Improving prediction of prostate cancer recurrence using chemical imaging

Precise Outcome prediction is crucial to providing optimal cancer care across the spectrum of solid cancers. Clinically-useful tools to predict risk of adverse events (metastases, recurrence), however, remain deficient. Here, we report an approach to predict the risk of prostate cancer recurrence, at the time of initial diagnosis, using a combination of emerging chemical imaging, a diagnostic protocol that focuses simultaneously on the tumor and its microenvironment, and data analysis of frequent patterns in molecular expression. Fourier transform infrared (FT-IR) spectroscopic imaging was employed to record the structure and molecular content from tumors prostatectomy. We analyzed data from a patient cohort that is mid-grade dominant – which is the largest cohort of patients in the modern era and in whom prognostic methods are largely ineffective. Our approach outperforms the two widely used tools, Kattan nomogram and CAPRA-S score in a head-to-head comparison for predicting risk of recurrence. Importantly, the approach provides a histologic basis to the prediction that identifies chemical and morphologic features in the tumor microenvironment that is independent of conventional clinical information, opening the door to similar advances in other solid tumors.

From sequence to molecular pathology, and a mechanism driving the neuroendocrine phenotype in prostate cancer

The current paradigm of cancer care relies on predictive nomograms which integrate detailed histopathology with clinical data. However, when predictions fail, the consequences for patients are often catastrophic, especially in prostate cancer where nomograms influence the decision to therapeutically intervene. We hypothesized that the high dimensional data afforded by massively parallel sequencing (MPS) is not only capable of providing biological insights, but may aid molecular pathology of prostate tumours. We assembled a cohort of six patients with high-risk disease, and performed deep RNA and shallow DNA sequencing in primary tumours and matched metastases where available. Our analysis identified copy number abnormalities, accurately profiled gene expression levels, and detected both differential splicing and expressed fusion genes. We revealed occult and potentially dormant metastases, unambiguously supporting the patients' clinical history, and implicated the REST transcriptional complex in the development of neuroendocrine prostate cancer, validating this finding in a large independent cohort. We massively expand on the number of novel fusion genes described in prostate cancer; provide fresh evidence for the growing link between fusion gene aetiology and gene expression profiles; and show the utility of fusion genes for molecular pathology. Finally, we identified chromothripsis in a patient with chronic prostatitis. Our results provide a strong foundation for further development of MPS-based molecular pathology.

A nomogram for individualized estimation of survival among patients with brain metastasis

PURPOSE

An estimated 24%-45% of patients with cancer develop brain metastases. Individualized estimation of survival for patients with brain metastasis could be useful for counseling patients on clinical outcomes and prognosis.

METHODS

De-identified data for 2367 patients with brain metastasis from 7 Radiation Therapy Oncology Group randomized trials were used to develop and internally validate a prognostic nomogram for estimation of survival among patients with brain metastasis. The prognostic accuracy for survival from 3 statistical approaches (Cox proportional hazards regression, recursive partitioning analysis [RPA], and random survival forests) was calculated using the concordance index. A nomogram for 12-month, 6-month, and median survival was generated using the most parsimonious model.

RESULTS

The majority of patients had lung cancer, controlled primary disease, no surgery, Karnofsky performance score (KPS) ≥ 70, and multiple brain metastases and were in RPA class II or had a Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) score of 1.25-2.5. The overall median survival was 136 days (95% confidence interval, 126-144 days). We built the nomogram using the model that included primary site and histology, status of primary disease, metastatic spread, age, KPS, and number of brain lesions. The potential use of individualized survival estimation is demonstrated by showing the heterogeneous distribution of the individual 12-month survival in each RPA class or DS-GPA score group.

CONCLUSION

Our nomogram provides individualized estimates of survival, compared with current RPA and DS-GPA group estimates. This tool could be useful for counseling patients with respect to clinical outcomes and prognosis.

External validation of nomogram for the prediction of recurrence after curative resection in early gastric cancer

BACKGROUND

Nomograms are statistics-based tools that provide the overall probability of a specific outcome. In our previous study, we developed a nomogram that predicts recurrence of early gastric cancer (EGC) after curative resection. We carried out this study to externally validate our EGC nomogram.

PATIENTS AND METHODS

The EGC nomogram was established from a retrospective EGC database that included 2923 consecutive patients. This nomogram was independently externally validated for a cohort of 1058 consecutive patients. For the EGC nomogram validation, we assessed both discrimination and calibration.

RESULTS

Within the follow-up period (median 37 months), a total of 11 patients (1.1%) experienced recurrence. The concordance index (c-index) was 0.7 (P = 0.02) and the result of the overall C index was 0.82 [P = 0.006, 95% confidence interval (CI) 0.59-1.00]. The goodness of fit test showed that the EGC nomogram had significantly good fit for 1- and 2-year survival intervals (P = 0.998 and 0.879, respectively). The actual and predicted survival outcomes showed good agreement, suggesting that the survival predictions from the nomogram are well calibrated externally.

CONCLUSIONS

A preexisting nomogram for predicting disease-free survival (DFS) of EGC after surgery was externally validated. The nomogram is useful for accurate and individual prediction of DFS, patient prognostication, counseling, and follow-up planning.

Validation of a nomogram for predicting overall survival after resection of pulmonary metastases from colorectal cancer at a single center

BACKGROUND

The goal of this study was to validate a survival nomogram at a single center, originally developed at multiple institutions in Japan, which combines readily available preoperative variables to predict overall survival after resection of pulmonary metastases from colorectal cancer.

METHODS

An external patient cohort from a prospective pulmonary metastases database at the Aichi Cancer Center in Japan was used to test the validity of the pulmonary metastases from a colorectal cancer nomogram. The cohort included 58 consecutive patients who had surgery between January 1999 and December 2005. Nomogram predictions for 3- and 5-year overall survival were calculated for each patient and compared with actual survival. The concordance index was used as an accuracy measure.

RESULTS

Data for all necessary variables were available for all patients. At the last follow-up, 30 patients were alive, with a median follow-up of 39 (range, 5-94) months. The 1-, 2-, 3-, and 5-year overall survival rates were 96.6, 84.5, 70.5, and 48.9%, respectively. The nomogram concordance index was 0.81 with excellent calibration for both 3- and 5-year overall survival rates.

CONCLUSIONS

The high predictive accuracy of pulmonary metastases from a colorectal cancer nomogram demonstrates that this predictive tool derived at multiple institutions can be applied to a small cohort of patients in a single center.

Beta-2-microglobulin expression correlates with high-grade prostate cancer and specific defects in androgen signaling

BACKGROUND

Previously, we identified Beta-2-microglobulin (beta2M) as an androgen-regulated secreted protein elevated in the serum of prostate cancer patients. In this study, we explore an interaction between beta2M expression, prostate cancer tissue, and the androgen signaling axis.

METHODS

beta2M expression in relation to clinical and pathologic variables was examined in a tissue microarray representing specimens obtained at the time of radical prostatectomy. Viral vectors were designed to down-regulate beta2M expression, and the effects on androgen-dependent growth, transcriptional regulation, and androgen receptor recruitment was investigated in human prostate cancer cell lines.

RESULTS

Variation in beta2M expression in human prostate cancer is associated with characteristics of clinically aggressive disease such as high tumor grade. Knockdown of beta2M expression in human prostate cancer cells resulted in selective defects in androgen-dependent events including growth, gene regulation, and chromatin assembly.

CONCLUSIONS

beta2M expression may provide prognostic information in patients treated with surgery for prostate cancer. Targeting beta2M expression or activity may represent a new and important mechanism to manipulate the androgen signaling axis in patients with prostate cancer.

Identification of a novel prostate cancer biomarker, caveolin-1: Implications and potential clinical benefit

While prostate cancer is a common disease in men, it is uncommonly life-threatening. To better understand this phenomenon, tumor biologists have sought to elucidate the mechanisms that contribute to the development of virulent prostate cancer. The recent discovery that caveolin-1 (Cav-1) functions as an important oncogene involved in prostate cancer progression reflects the success of this effort. Cav-1 is a major structural coat protein of caveolae, specialized plasma membrane invaginations involved in multiple cellular functions, including molecular transport, cell adhesion, and signal transduction. Cav-1 is aberrantly overexpressed in human prostate cancer, with higher levels evident in metastatic versus primary sites. Intracellular Cav-1 promotes cell survival through activation of Akt and enhancement of additional growth factor pro-survival pathways. Cav-1 is also secreted as a biologically active molecule that promotes cell survival and angiogenesis within the tumor microenvironment. Secreted Cav-1 can be reproducibly detected in peripheral blood using a sensitive and specific immunoassay. Cav-1 levels distinguish men with prostate cancer from normal controls, and preoperative Cav-1 levels predict which patients are at highest risk for relapse following radical prostatectomy for localized disease. Thus, secreted Cav-1 is a promising biomarker in identifying clinically significant prostate cancer.

Identification of a novel prostate cancer biomarker, caveolin-1: Implications and potential clinical benefit

While prostate cancer is a common disease in men, it is uncommonly life-threatening. To better understand this phenomenon, tumor biologists have sought to elucidate the mechanisms that contribute to the development of virulent prostate cancer. The recent discovery that caveolin-1 (Cav-1) functions as an important oncogene involved in prostate cancer progression reflects the success of this effort. Cav-1 is a major structural coat protein of caveolae, specialized plasma membrane invaginations involved in multiple cellular functions, including molecular transport, cell adhesion, and signal transduction. Cav-1 is aberrantly overexpressed in human prostate cancer, with higher levels evident in metastatic versus primary sites. Intracellular Cav-1 promotes cell survival through activation of Akt and enhancement of additional growth factor pro-survival pathways. Cav-1 is also secreted as a biologically active molecule that promotes cell survival and angiogenesis within the tumor microenvironment. Secreted Cav-1 can be reproducibly detected in peripheral blood using a sensitive and specific immunoassay. Cav-1 levels distinguish men with prostate cancer from normal controls, and preoperative Cav-1 levels predict which patients are at highest risk for relapse following radical prostatectomy for localized disease. Thus, secreted Cav-1 is a promising biomarker in identifying clinically significant prostate cancer.

Critical review of prostate cancer predictive tools

Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities and potential treatment-related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, look-up and propensity scoring tables, risk-class stratification prediction tools, classification and regression tree analysis, nomograms and artificial neural networks. Criteria to evaluate tools include discrimination, calibration, generalizability, level of complexity, decision analysis and ability to account for competing risks and conditional probabilities. The available predictive tools and their features, with a focus on nomograms, are described. While some tools are well-calibrated, few have been externally validated or directly compared with other tools. In addition, the clinical consequences of applying predictive tools need thorough assessment. Nevertheless, predictive tools can facilitate medical decision-making by showing patients tailored predictions of their outcomes with various alternatives. Additionally, accurate tools may improve clinical trial design.

Stage migration in localized prostate cancer has no effect on the post-radical prostatectomy Kattan nomogram

OBJECTIVE

To investigate the effect of prostate-specific antigen (PSA) testing on stage migration in an Australian population, and its consequences on the prognostic accuracy of the post-radical prostatectomy (RP) Kattan nomogram, as in North America widespread PSA testing has resulted in prostate cancer stage migration, questioning the utility of prognostic nomograms in this setting.

PATIENTS AND METHODS

The study comprised 1008 men who had consecutive RP for localized prostate cancer between 1991 and 2001 at one institution. Two groups were assessed, i.e. those treated in 1991-96 (group 1, the early PSA era), and 1997-2001 (group 2, the contemporary PSA era). Differences in clinicopathological features between the groups were analysed by chi-squared testing and survival modelling. Individual patient data were entered into the post-RP Kattan nomogram and the efficacy assessed by receiver- operating characteristic curve analysis.

RESULTS

Patients in group 2 had lower pathological stage disease (P = 0.01) and fewer cancers with Gleason score > or =8 (P < 0.001) than group 1. Multivariate analysis identified preoperative serum PSA level (P < 0.01) and Gleason score (P < 0.01) as strong predictors of biochemical relapse in both groups. In group 2 pathological stage was not significant, but margin involvement became highly significant (P = 0.004). There was no difference in the predictive accuracy of the Kattan nomogram between the groups (P = 0.253).

CONCLUSIONS

These findings show a downward stage migration towards organ-confined disease after the introduction of widespread PSA testing in an Australian cohort. Despite this, the Kattan nomogram remains a robust prognostic tool in clinical practice.

Nomograms for staging, prognosis, and predicting treatment outcomes

Prostate cancer is a heterogeneous disease with a wide prognostic spectrum and a variety of treatment options. Such a complex clinical scenario has led to uncertainty in risk assessment and prediction of outcome. Nomograms have served as scientific formulas designed to maximize the predictive accuracy. The use of nomograms in prostate cancer has been applied to many clinical states and outcomes and has provided the most accurate predictions. Cancer 2009;115(13 suppl):3107-11. (c) 2009 American Cancer Society.

Cost effectiveness of risk-prediction tools in selecting patients for immediate post-prostatectomy treatment

BACKGROUND AND OBJECTIVE

Ideally, tests that predict the risk of cancer recurrence should be capable of guiding treatment decisions that are both therapeutically effective and cost effective. This paper evaluates the cost effectiveness of two tools that identify patients at high risk for biochemical (prostate-specific antigen) recurrence of prostate cancer after prostatectomy, the hypothesis being that accurate classification of high-risk patients will allow more appropriate use of secondary (adjuvant/salvage) treatment and may improve on current clinical practice. These risk-prediction tools are the Kattan postoperative nomogram, which uses clinicopathologic features, and the Prostate Px test, which employs additional morphometric and immunofluorescence features of the prostate specimen to predict risk of biochemical recurrence. These tools were trained on patients treated at the Memorial Sloan-Kettering Cancer Center (996 patients for the nomogram, 342 patients for the Prostate Px test).

METHODS

The cost effectiveness of the Prostate Px test, the Kattan postoperative nomogram, and current clinical practice were compared using a decision analytic model. The modeled treatment for low-risk patients was watchful waiting. The modeled treatments for high-risk patients were local radiation, hormonal therapy, and watchful waiting. Costs, utilities, and transition probabilities were obtained from the literature. Costs and effects were discounted at 3% per year. The time span modeled was 10 years after prostatectomy. Monte Carlo simulation was performed to estimate cost and effectiveness; sensitivity analysis was performed to examine the impact of uncertainty in the parameter values.

RESULTS

The expected quality-adjusted life years (QALYs) for the Prostate Px test, nomogram, and current practice were 8.11, 7.39, and 6.47, respectively. The expected costs were $US17 549, $US14 162, and $US14 104, respectively. The incremental cost-effectiveness ratio of the Prostate Px was $US4704/QALY compared with the nomogram, and $US2100/QALY compared with current practice. The incremental cost-effectiveness ratio of the nomogram was $US63/QALY compared with current practice. These ratios are well below the common willingness-to-pay limit of $US50 000/QALY. Expected effectiveness was highest for the Prostate Px test, followed by the nomogram. Expected cost was slightly higher for Prostate Px than for either alternative; nevertheless, the Prostate Px was cost effective compared with both the nomogram and current practice. The nomogram was cost effective compared with current practice. The acceptable cost effectiveness of the Prostate Px test and the nomogram compared with current practice were not sensitive to changes in the values used to inform the model within clinically plausible ranges. The superior performance of both Prostate Px test and nomogram over current practice resulted from identifying high-risk patients likely to benefit from adjuvant treatment, while sparing the low-risk patients the added cost and toxicity of treatment.

CONCLUSION

Incorporation of risk-prediction tools in the initial management of patients after prostatectomy resulted in increased QALYs at an acceptable increase in cost relative to current practice.

Prediction of prostate cancer recurrence using magnetic resonance imaging and molecular profiles

PURPOSE

To evaluate whether pretreatment magnetic resonance imaging (MRI)/MR spectroscopic imaging (MRSI) findings and molecular markers in surgical specimens correlate with each other and with pretreatment clinical variables (biopsy Gleason score, clinical stage, and prostate-specific antigen level) and whether they contribute incremental value in predicting prostate cancer recurrence.

EXPERIMENTAL DESIGN

Eighty-eight prostate cancer patients underwent MRI/MRSI before radical prostatectomy; imaging findings were scored on a scale of 1 to 7 (no tumor seen-lymph node metastasis). Ki-67, phospho-Akt, and androgen receptor expression in surgical specimens were assessed by immunohistochemistry. To examine correlations between markers and imaging scores, Spearman's correlation was used. To test whether markers and imaging scores differed by clinical stage or Gleason score, Wilcoxon's rank sum test was used. To examine time to recurrence, the methods of Kaplan-Meier were used. Cox proportional hazards models were built and their concordance indices (C-indices) were calculated to evaluate prediction of recurrence.

RESULTS

All markers correlated moderately strongly with MRI/MRSI score (all correlation coefficients >0.5). Markers and MRI/MRSI score were strongly associated with clinical stage and biopsy Gleason score (P < 0.01 for all). At last follow-up, 27 patients had recurrence. C-indices for MRI/MRSI score and all markers were associated with time to recurrence and ranged from 0.78 to 0.89. A Cox model combining all clinical predictors had a C-index of 0.89; the C-index increased to 0.95 when MRI/MRSI score was added and to 0.97 when markers were also added.

CONCLUSIONS

MRI/MRSI findings and molecular markers correlated well with each other and contributed incremental value to clinical variables in predicting prostate cancer recurrence.

Validation of a nomogram for predicting survival after resection for adenocarcinoma of the pancreas

Background

Nomograms are statistical tools providing the overall probability of a specific outcome; they have shown better individual discrimination than the tumour node metastasis staging system in several cancers. The pancreatic nomogram, originally developed in the Memorial Sloan–Kettering Cancer Center (MSKCC) in the USA, combines clinicopathological and operative data to predict disease-specific survival at 1, 2 and 3 years from initial resection.

Methods

An external patient cohort from a retrospective pancreatic adenocarcinoma database at the Academic Medical Centre in Amsterdam was used to test the validity of the pancreatic adenocarcinoma nomogram. The cohort included 263 consecutive patients who had surgery between January 1985 and December 2004.

Results

Data for all the necessary variables were available for 256 patients (97·3 per cent). At the last follow-up, 35 patients were alive, with a median follow-up of 27 (range 3–114) months. The 1-, 2- and 3-year disease-specific survival rates were 60·8, 30·4 and 16·0 per cent respectively. The nomogram concordance index was 0·61. The calibration analysis of the model showed that the predicted survival did not significantly deviate from the actual survival.

Conclusion

The MSKCC pancreatic cancer nomogram provided an accurate survival prediction. It may aid in counselling patients and in stratification of patients for clinical trials.

Nomogram for deciding adjuvant treatment after surgery for oral cavity squamous cell carcinoma

BACKGROUND

The application of appropriate adjuvant treatment after surgery for oral cavity squamous cell carcinoma (OCSCC) is predicated on accurate patient risk stratification.

METHODS

A nomogram for estimating locoregional recurrence-free survival (LRFS) after treatment of OCSCC was constructed from a cohort of 590 patients with OCSCC who were treated at Memorial Sloan-Kettering Cancer Center (MSKCC). The nomogram was validated using a series of 417 patients with OCSCC who were treated at Hospital do Cancer AC Camargo (HACC) in São Paulo, Brazil.

RESULTS

Despite significant differences between the MSKCC and HACC cohorts, the nomogram was able to predict LRFS from OCSCC with a concordance index of 0.693. Further statistical analysis showed that the nomogram was well calibrated.

CONCLUSIONS

This preliminary nomogram is the first prognostic model developed and externally validated to predict the likelihood of LRFS after treatment for an individual patient with OCSCC and may have practical utility for deciding adjuvant treatment.

Prediction of graft survival of living-donor kidney transplantation: nomograms or artificial neural networks?

BACKGROUND

An artificial neural networks (ANNs) model was developed to predict 5-year graft survival of living-donor kidney transplants. Predictions from the validated ANNs were compared with Cox regression-based nomogram.

METHODS

Out of 1900 patients with living-donor kidney transplant; 1581 patients were used for training of the ANNs (training group), the remainder 319 patients were used for its validation (testing group). Many variables were correlated with the graft survival by univariate analysis. Significant ones were used for ANNs construction of a predictive model. The same variables were subjected to a multivariate statistics using Cox regression model; their result was the basis of a nomogram construction. The ANNs predictive model and the nomogram were used to predict the graft survival of the testing group. The predicted probability(s) was compared with the actual survival estimates.

RESULTS

The ANNs sensitivity was 88.43% (95% confidence interval [CI] 86.4-90.3), specificity was 73.26% (95% CI 70-76.3), and predictive accuracy was 88% (95% CI 87-90) in the testing group, whereas nomogram sensitivity was 61.84% (95% CI 50-72.8) with 74.9% (95% CI 69-80.2) specificity and predictive accuracy was 72% (95% CI 67-77). The positive predictive value of graft survival was 82.1% and 43.5% for the ANNs and Cox regression-based nomogram, respectively, and the negative predictive value was 82% and 86.3% for the ANNs and Cox regression-based nomogram, respectively. Predictions by both models fitted well with the observed findings.

CONCLUSIONS

These results suggest that ANNs was more accurate and sensitive than Cox regression-based nomogram in predicting 5-year graft survival.

Inventory of prostate cancer predictive tools

PURPOSE OF REVIEW

We created an inventory of current predictive tools available for prostate cancer. This review may serve as an initial step toward a comprehensive reference guide for physicians to locate published nomograms that apply to the clinical decision in question. Using MEDLINE a literature search was performed on prostate cancer predictive tools from January 1966 to November 2007. We describe the patient populations to which they apply and the outcomes predicted, and record their individual characteristics.

RECENT FINDINGS

The literature search generated 111 published prediction tools that may be applied to patients in various clinical stages of disease. Of the 111 prediction tools, only 69 had undergone validation. We present an inventory of models with input variables, prediction form, number of patients used to develop the prediction tools, the outcome being predicted, prediction tool-specific features, predictive accuracy, and whether validation was performed.

SUMMARY

Decision rules, such as nomograms, provide evidence-based and at the same time individualized predictions of the outcome of interest. Such predictions have been repeatedly shown to be more accurate than those of clinicians, regardless of their level of expertise. Accurate risk estimates are also required for clinical trial design, to ensure homogeneous high-risk patient groups for whom new cancer therapeutics will be investigated.

External validation of a biomarker-based preoperative nomogram predicts biochemical recurrence after radical prostatectomy

PURPOSE

Biomarker signatures currently are used in several malignancies to guide clinical decision making. Recently, preoperative plasma levels of transforming growth factor-beta1 (TGF-beta1) and interleukin-6 soluble receptor (IL6-SR) have improved the accuracy of a clinical nomogram that predicted biochemical recurrence after radical prostatectomy. However, this model was never externally validated. We tested the accuracy of this nomogram in an independent, external cohort.

PATIENTS AND METHODS

Preoperative plasma levels of TGF-beta1 and IL6-SR were measured in 423 consecutive men who underwent radical prostatectomy and bilateral lymphadenectomy and were used, along with preoperative prostate-specific antigen levels, biopsy Gleason sum, and clinical stage to determine nomogram-derived probabilities of biochemical recurrence-free survival at 5 years after radical prostatectomy. The accuracy of predictions was quantified with the area under the curve (AUC) and calibration plots that graphically displayed the nomogram's performance characteristics. The statistical significance of the difference between the biomarker nomogram and a model designed on the basis of clinical variables alone was tested by using the Mantel-Haenszel statistic.

RESULTS

Biochemical recurrence-free survival at 5 years was 77.0% (95% CI, 72.0% to 82.0%). The biomarker-based nomogram was 87.9% accurate versus 71.1% for the nomogram designed on the basis of clinical variables alone (16.8% difference; P < .001). The performance characteristics of the biomarker-based nomogram were superior to those of the clinical nomogram.

CONCLUSION

We confirm that plasma levels of TGF-beta1 and IL6-SR considerably enhance the accuracy of the standard preoperative nomogram for the prediction of biochemical recurrence after radical prostatectomy. This model further refines our ability to identify patients at a high risk of biochemical recurrence after radical prostatectomy.

Improved prediction of prostate cancer recurrence through systems pathology

We have developed an integrated, multidisciplinary methodology, termed systems pathology, to generate highly accurate predictive tools for complex diseases, using prostate cancer for the prototype. To predict the recurrence of prostate cancer following radical prostatectomy, defined by rising serum prostate-specific antigen (PSA), we used machine learning to develop a model based on clinicopathologic variables, histologic tumor characteristics, and cell type-specific quantification of biomarkers. The initial study was based on a cohort of 323 patients and identified that high levels of the androgen receptor, as detected by immunohistochemistry, were associated with a reduced time to PSA recurrence. The model predicted recurrence with high accuracy, as indicated by a concordance index in the validation set of 0.82, sensitivity of 96%, and specificity of 72%. We extended this approach, employing quantitative multiplex immunofluorescence, on an expanded cohort of 682 patients. The model again predicted PSA recurrence with high accuracy, concordance index being 0.77, sensitivity of 77% and specificity of 72%. The androgen receptor was selected, along with 5 clinicopathologic features (seminal vesicle invasion, biopsy Gleason score, extracapsular extension, preoperative PSA, and dominant prostatectomy Gleason grade) as well as 2 histologic features (texture of epithelial nuclei and cytoplasm in tumor only regions). This robust platform has broad applications in patient diagnosis, treatment management, and prognostication.

Association of cysteine-rich secretory protein 3 and beta-microseminoprotein with outcome after radical prostatectomy

PURPOSE

It has been suggested that cysteine-rich secretory protein 3 (CRISP-3) and beta-microseminoprotein (MSP) are associated with outcome in prostate cancer. We investigated whether these markers are related to biochemical recurrence and whether addition of the markers improves prediction of recurring disease.

EXPERIMENTAL DESIGN

Tissue microarrays of radical prostatectomy specimens were analyzed for CRISP-3 and MSP by immunohistochemistry. Associations between marker positivity and postprostatectomy biochemical recurrence [prostate-specific antigen (PSA) >0.2 ng/mL with a confirmatory level] were evaluated by univariate and multivariable Cox proportional hazards regression. Multivariable analyses controlled for preoperative PSA and pathologic stage and grade.

RESULTS

Among 945 patients, 224 had recurrence. Median follow-up for survivors was 6.0 years. Patients positive for CRISP-3 had smaller recurrence-free probabilities, whereas MSP-positive patients had larger recurrence-free probabilities. On univariate analysis, the hazard ratio for patients positive versus negative for CRISP-3 was 1.53 (P=0.010) and for MSP was 0.63 (P=0.004). On multivariable analysis, both CRISP-3 (P=0.007) and MSP (P=0.002) were associated with recurrence. The hazard ratio among CRISP-3-positive/MSP-negative patients compared with CRISP-3-negative/MSP-positive patients was 2.38. Adding CRISP-3 to a base model that included PSA and pathologic stage and grade did not enhance the prediction of recurrence, but adding MSP increased the concordance index minimally from 0.778 to 0.781.

CONCLUSION

We report evidence that CRISP-3 and MSP are independent predictors of recurrence after radical prostatectomy for localized prostate cancer. However, addition of the markers does not importantly improve the performance of existing predictive models. Further research should aim to elucidate the functions of CRISP-3 and MSP in prostate cancer cells.

Role of nomograms for prostate cancer in 2007

Nomograms have been developed to predict prostate cancer (PCa) related outcomes. We report what has been achieved and what can be expected in 2007 and in the future. We reviewed the literature to provide guidelines in terms of criteria, limitations and clinical value of nomograms in 2007. Further, we report a set of recent PCa nomograms, where certain criteria are listed which were used to develop each nomogram. Our findings suggest a demand for an update of nomograms as well as head-to-head comparisons to determine the best-suited model in select fields of PCa outcomes. In 2007 and the future, an increasing number of nomograms will address important endpoints such as PSA recurrence, local and distant metastases, or androgen-independent PCa-specific survival. Our results suggest that nomograms represent valid risk stratification models to achieve most accurate predictions. In 2007 and the future, more specific and refined nomograms will be available which address relevant clinical end points. Moreover, novel markers in PCa outcomes will be quantified using the nomogram approach.

Key issues in handling and reporting radical prostatectomy specimens

CONTEXT

Patients with prostatic adenocarcinoma commonly undergo radical prostatectomy, and it is often difficult and time consuming to handle the resulting specimens and to report the findings. Pathologic information derived from the radical prostatectomy specimen is used for selecting adjuvant therapy, such as radiotherapy and hormone therapy, and for determining a patient's prognosis. The prostate specimen must be handled in a systematic fashion to derive the appropriate prognostic parameters.

OBJECTIVE

To review the prognostic factors of relevance in classifying radical prostatectomy specimens, using the College of American Pathologists categorization system, including a detailed survey of the morphologic-based factors but excluding other factors such as DNA ploidy and novel phenotypic and genotypic markers.

CONCLUSIONS

Gleason score, pathologic stage, and margin status are considered category 1 prognostic factors, which are of proven prognostic significance and are useful in patient management. Factors such as tumor volume (intraglandular extent) and tumor subtype are considered category 2 prognostic factors, which show significant promise but require validation in multivariate analysis. Lymphovascular space invasion is a promising category 3 prognostic factor that needs additional study. Perineural invasion is an almost ubiquitous finding in radical prostatectomy specimens and is considered a category 3 prognostic factor. After prognostic factors have been analyzed at the histologic level, it is critical to report the findings in a clear and unambiguous fashion. The synoptic style of reporting is ideal for describing complex cancer resection specimens. A synoptic report based on an evidence-based checklist, such as the one developed by the College of American Pathologists, effectively communicates complex cancer-related data, such as radical prostatectomy specimen findings. This information is used not only for individual case management with respect to treatment and prognostication but also for purposes such as education, research, quality monitoring, and system planning.

Chemotherapy for prostate cancer: implementing early systemic therapy to improve outcomes

Prostate cancer remains a significant health concern for men in the USA as it is a leading cancer diagnosis and a cause of death. With the use of prostate-specific antigen or screening, a stage migration has occurred with an increase in the number of men diagnosed with early-stage disease. The optimal primary management of these men is evolving, but despite adequate local treatment a significant percentage will develop either biochemical or clinical evidence of recurrent disease. Several criteria for risk stratification have been developed, thus, improving the ability to identify a high-risk population. Small studies have been reported demonstrating the feasibility of neoadjuvant or adjuvant chemotherapy in conjunction with either radiation or radical prostatectomy in this high-risk population, and large phase III studies are ongoing. With the advent of life-prolonging chemotherapy in the hormone-refractory setting, attention must now also be given to early-stage disease so as to develop multi-modality approaches with the hope of increasing survival and ultimately providing a cure.

Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy

PURPOSE

A postoperative nomogram for prostate cancer recurrence after radical prostatectomy (RP) has been independently validated as accurate and discriminating. We have updated the nomogram by extending the predictions to 10 years after RP and have enabled the nomogram predictions to be adjusted for the disease-free interval that a patient has maintained after RP.

METHODS

Cox regression analysis was used to model the clinical information for 1,881 patients who underwent RP for clinically-localized prostate cancer by two high-volume surgeons. The model was externally validated separately on two independent cohorts of 1,782 patients and 1,357 patients, respectively. Disease progression was defined as a rising prostate-specific antigen (PSA) level, clinical progression, radiotherapy more than 12 months postoperatively, or initiation of systemic therapy.

RESULTS

The 10-year progression-free probability for the modeling set was 79% (95% CI, 75% to 82%). Significant variables in the multivariable model included PSA (P = .002), primary (P < .0001) and secondary Gleason grade (P = .0006), extracapsular extension (P < .0001), positive surgical margins (P = .028), seminal vesicle invasion (P < .0001), lymph node involvement (P = .030), treatment year (P = .008), and adjuvant radiotherapy (P = .046). The concordance index of the nomogram when applied to the independent validation sets was 0.81 and 0.79.

CONCLUSION

We have developed and validated as a robust predictive model an enhanced postoperative nomogram for prostate cancer recurrence after RP. Unique to predictive models, the nomogram predictions can be adjusted for the disease-free interval that a patient has achieved after RP.

Integration of gene expression profiling and clinical variables to predict prostate carcinoma recurrence after radical prostatectomy

BACKGROUND

Gene expression profiling of prostate carcinoma offers an alternative means to distinguish aggressive tumor biology and may improve the accuracy of outcome prediction for patients with prostate carcinoma treated by radical prostatectomy.

METHODS

Gene expression differences between 37 recurrent and 42 nonrecurrent primary prostate tumor specimens were analyzed by oligonucleotide microarrays. Two logistic regression modeling approaches were used to predict prostate carcinoma recurrence after radical prostatectomy. One approach was based exclusively on gene expression differences between the two classes. The second approach integrated prognostic gene variables with a validated postoperative predictive model based on standard variables (nomogram). The predictive accuracy of these modeling approaches was evaluated by leave-one-out cross-validation (LOOCV) and compared with the nomogram.

RESULTS

The modeling approach using gene variables alone accurately classified 59 (75%) tissue samples in LOOCV, a classification rate substantially higher than expected by chance. However, this predictive accuracy was inferior to the nomogram (concordance index, 0.75 vs. 0.84, P = 0.01). Models combining clinical and gene variables accurately classified 70 (89%) tissue samples and the predictive accuracy using this approach (concordance index, 0.89) was superior to the nomogram (P = 0.009) and models based on gene variables alone (P < 0.001). Importantly, the combined approach provided a marked improvement for patients whose nomogram-predicted likelihood of disease recurrence was in the indeterminate range (7-year disease progression-free probability, 30-70%; concordance index, 0.83 vs. 0.59, P = 0.01).

CONCLUSIONS

Integration of gene expression signatures and clinical variables produced predictive models for prostate carcinoma recurrence that perform significantly better than those based on either clinical variables or gene expression information alone.

Development and validation of a nomogram predicting the outcome of prostate biopsy based on patient age, digital rectal examination and serum prostate specific antigen

PURPOSE

We developed and validated a nomogram which predicts presence of prostate cancer (PCa) on needle biopsy.

MATERIALS AND METHODS

We used 3 cohorts of men who were evaluated with sextant biopsy of the prostate and whose presenting prostate specific antigen (PSA) was not greater than 50 ng/ml. Data from 4,193 men from Montreal, Canada were used to develop a nomogram based on age, digital rectal examination (DRE) and serum PSA. External validation was performed on 1,762 men from Hamburg, Germany. Data from these men were subsequently used to develop a second nomogram in which percent free PSA (%fPSA) was added as a predictor. External validation was performed using 514 men from Montreal. Both nomograms were based on multivariate logistic regression models. Predictive accuracy was evaluated with areas under the receiver operating characteristic curve and graphically with loess smoothing plots.

RESULTS

PCa was detected in 1,477 (35.2%) men from Montreal, 739 (41.9%) men from Hamburg and 189 (36.8%) men from Montreal. In all models all predictors were significant at 0.05. Using age, DRE and PSA external validation AUC was 0.69. Using age, DRE, PSA and %fPSA external validation AUC was 0.77.

CONCLUSIONS

A nomogram based on age, DRE, PSA and %fPSA can highly accurately predict the outcome of prostate biopsy in men at risk for PCa.

When and how to use informatics tools in caring for urologic patients

Making predictions is an essential part of any medical decision. It is particularly crucial when considering treatment of clinically localized prostate cancer. Nomograms and prediction model software typically provide the most accurate predictions. Many nomograms have been developed, for all prostate cancer clinical states. Some of these are discussed in this review, as is their utility in facilitating decision making and informed consent.

Current Recommendations for Delaying Renal Transplantation after Localized Prostate Cancer Treatment: Are They Still Appropriate?

BACKGROUND

Since the advent of prostate-specific antigen (PSA) testing, most men diagnosed with prostate cancer (PC) have localized disease, which is curable with surgery or radiation therapy. Current policy for patients with end-stage renal disease (ESRD) and PC recommends waiting 5 years after primary therapy before enrollment on the transplant waiting list. The risk of dying during 5 years of dialysis is approximately 59%, whereas the risk of PC recurrence after surgery is generally much lower. Prognostic tools called nomograms can accurately assess a patient's probability of PC recurrence. This prompted the authors to reexamine current transplantation policy for patients with PC.

METHODS

The authors reviewed the Sloan-Kettering PC database to identify patients on dialysis undergoing radical prostatectomy. Clinical and pathologic features were analyzed to determine the likelihood of disease recurrence.

RESULTS

The authors identified two patients with ESRD in their PC database. Both men had elevated serum PSA detected during routine pretransplantation evaluation, and biopsy confirmed the PC. Both opted for surgery, with pathologic analysis revealing organ-confined disease and negative surgical margins. The postoperative nomogram predicted 7-year progression-free probabilities of 95% and 98%. Given the high likelihood of cure of their PC, immediate consideration for renal transplantation seemed appropriate for both patients.

CONCLUSIONS

PSA-based screening of the dialysis population has ensured earlier detection of PC. Given that nomograms will accurately predict the risk of PC recurrence, the time a patient must wait for a transplant should be based on this individualized risk assessment rather than on a general rule.

Prognostic significance of Gleason pattern in patients with Gleason score 7 prostate carcinoma

BACKGROUND

In the current study, the authors sought to further stratify the prognosis of patients with Gleason score (GS) 7 prostate carcinoma. They assessed the influence on outcome of a predominant poorly differentiated Gleason pattern (primary Gleason pattern [GP] 4) and/or a coincident small focus of poorly differentiated tumor of higher grade (tertiary GP 5).

METHODS

The authors studied 412 patients (mean postoperative follow-up, 33 months) with GS 7 tumors treated with radical prostatectomy at a single Australian campus between November 1989 and December 2002. The chi-square test, Kaplan-Meier method, and Cox proportional hazards analyses were used to evaluate the correlation between primary GP 4 and tertiary GP 5 with the occurrence of adverse pathologic features and disease recurrence.

RESULTS

In this cohort, 307 patients (75%) had primary GP 3 tumors, 105 (25%) had primary GP 4 tumors, and 17 (2.3%) had a tertiary element of high-grade tumor (GP 5). Patients with primary GP 4 tumors displayed higher rates of seminal vesicle involvement and extraprostatic extension and, along with patients with tertiary GP 5, had significantly shorter times to disease recurrence. Univariate analysis demonstrated that primary GP 4 (P = 0.0003) and tertiary GP 5 (P < 0.0001) were strong predictors of disease recurrence. Primary GP 4 (P = 0.0122) remained an independent predictor of disease recurrence on stepwise multivariate analysis.

CONCLUSIONS

Primary GP 4 tumors represented an aggressive subset of GS 7 prostate carcinomas. Primary GP was an easily accessible and clinically relevant predictor of disease recurrence in patients with GS 7 prostate carcinoma.

Preoperative Prediction of Pathological Stage by Quantitative Histology in 102 Patients with Prostate Cancer (PCa) and Serum PSA ≤10 ng/mL

Purpose. To find a predictor of extraprostatic extension in clinically localized prostate cancer (PCa), preoperative ultrasound-guided prostate needle biopsies and clinicopathological data were reviewed.

Materials and Methods

102 consecutive patients (median age 63 years) with serum PSA ≤10 ng/mL who underwent radical retropubic prostatectomy were included. Preoperative prostate biopsies according to an extended protocol were performed and whole-mount prostatectomy specimens were processed. One or more of the following biopsy variables were considered predictive of locally andvanced PCa: more than 2/12 cancer-positive cores, total percentage of cancer (TPC) >20%, greatest percentage of cancer (GPC) >50%, bilateral PCa, presence of cancer in both lateral portions, Gleason score >6.

Results

Only 32/102 (31.4%) specimens showed an organ-confined PCa; the remaining were pT3a in 30 (29.4%) cases, pT3b in 6 (5.9%) and pT2–T3 with positive surgical margins in 34 (33.3%). Quantitative histology predicted an organ-confined PCa in 41.2% of patients. In all 102 patients and in 56 with T1c clinical stage, the positive predictive value (PPV) and negative predictive value (NPV) of biopsy findings, to predict an organ confined PCa, was 81.2 vs 92% and 91.6 vs 93.4%, respectively. The PPV and NPV to predict a locally advanced PCa was 92.8 and 86.5%, respectively.

Conclusions

Quantitative histology seems to be helpful for locally staging of PCa in patients with T1c clinical stage and PSA ≤10 ng/mL.

Validation of the postoperative nomogram for 12-year sarcoma-specific mortality

BACKGROUND

On the basis of a prospectively followed cohort of adult patients with primary soft tissue sarcoma (STS) who were treated at Memorial Sloan-Kettering Cancer Center (MSKCC; New York, NY), a nomogram for predicting sarcoma-specific mortality was developed. Although this nomogram was found to be accurate by internal validation tests, it had not been validated in an external patient cohort, and thus its universal applicability remained unproven.

METHODS

Between 1975 and 2002, 1167 adult patients (age > or = 16 years) underwent treatment for primary STS at the University of California-Los Angeles (UCLA; Los Angeles, CA). All patients treated with an ifosfamide-based chemotherapy protocol (n = 238) were excluded from the current analysis. The remaining 929 patients constituted the population on which the validation study was performed. The nomogram validation process comprised two activities. First, the extent of discrimination was quantified using the concordance index. Second, the level of calibration was assessed by grouping patients with respect to their nomogram-predicted mortality probabilities and then comparing group means with observed Kaplan-Meier estimates of disease-specific survival.

RESULTS

With median follow-up intervals of 48 months for all patients and 60 months for surviving patients, the 5-year and 10-year disease-specific survival rates were 77% (95% confidence interval [CI], 74-80%) and 71% (95% CI, 67-75%), respectively. Application of the nomogram to the UCLA data set yielded a concordance index of 0.76, and the observed correspondence between predicted and actual outcomes suggested a high level of calibration.

CONCLUSIONS

In the current study, the MSKCC Sarcoma Nomogram was found to provide accurate survival predictions when it was applied to an external cohort of patients who were treated at UCLA.

Postoperative nomogram for disease-specific survival after an R0 resection for gastric carcinoma

PURPOSE

Few published studies have addressed individual patient risk after R0 resection for gastric cancer. We developed and internally validated a nomogram that combines these factors to predict the probability of 5-year gastric cancer-specific survival on the basis of 1,039 patients treated at a single institution.

METHODS

Nomogram predictor variables included age, sex, primary site (distal one-third, middle one-third, gastroesophageal junction, and proximal one-third), Lauren histotype (diffuse, intestinal, mixed), number of positive lymph nodes resected, number of negative lymph nodes resected, and depth of invasion. Death as a result of gastric cancer was the predicted end point. The concordance index was used as an accuracy measure, with bootstrapping to correct for optimistic bias. Calibration plots were constructed.

RESULTS

Gastric cancer-specific survival at 5 years was 50%. A nomogram was constructed on the basis of a Cox regression model. The bootstrap-corrected concordance index was 0.80. When compared with the predictive ability of American Joint Committee on Cancer stage, the nomogram discrimination was superior (P <.001). Nomogram calibration appeared to be excellent.

CONCLUSION

A nomogram was developed to predict 5-year disease-specific survival after R0 resection for gastric cancer. This tool should be useful for patient counseling, follow-up scheduling, and clinical trial eligibility determination.

Indium-111-capromab pendetide radioimmunoscintigraphy and prognosis for durable biochemical response to salvage radiation therapy in men after failed prostatectomy

PURPOSE

We evaluated the prognostic significance of indium-111 (111In)-capromab pendetide imaging for patients with prostate cancer who underwent salvage radiotherapy (RT) for recurrent disease after prostatectomy.

PATIENTS AND METHODS

Records were reviewed for all men who underwent 111In-capromab pendetide imaging at a single institution from February 1997 through December 1999. We identified 30 eligible men who were radiographically negative for metastatic disease, who had increasing serum prostate-specific antigen (PSA) after primary radical prostatectomy, and who received salvage RT. Clinical interpretations of indium monoclonal antibody (In-mab) scan results were compared with postsalvage RT PSA response.

RESULTS

Using an American Society of Therapeutic Radiation and Oncology definition of PSA failure, in men with a positive scan in at least one location (n = 14), the cumulative 2-year PSA control after salvage RT was 0.38 +/- 0.13 (+/- SE) compared with 0.31 +/- 0.13 for men with a normal antibody scan in and outside the prostate fossa (n = 15; proportional hazard ratio [PHR] = 1.32; 95% confidence interval [CI], 0.52 to 3.36). For men with a positive antibody scan limited to the prostate fossa (n = 9), PSA control at 2 years was 0.13 +/- 0.12 (PHR 1.77; 95% CI, 0.65 to 4.85). The 2-year probability of PSA control after salvage RT for men with positive scan results outside the prostate bed irrespective of In-mab findings in the prostate fossa (n = 5) was 0.60 +/- 0.22 (PHR 0.81; 95% CI, 0.17 to 3.78).

CONCLUSION

In contrast to previous reports, for patients with postprostatectomy biochemical relapse who received salvage RT, presalvage RT In-mab scan findings outside the prostate fossa were not predictive of biochemical control after RT.