Cardiac amyloidosis imaging with amyloid positron emission tomography: A systematic review and meta-analysis.

BACKGROUND: Recent progress in amyloid positron emission tomography (PET) has enabled the targeted imaging of cardiac amyloidosis with accuracy. We performed a systematic review and meta-analysis on the diagnostic performance of cardiac amyloidosis using amyloid PET. METHODS: A systematic search was performed using key words: cardiac amyloidosis, amyloid, and PET. We estimated the pooled sensitivity, specificity, positive and negative likelihood ratio (LR), and diagnostic odds ratio (DOR). Furthermore, the semiquantitative parameters of PET were evaluated to diagnose cardiac amyloidosis and discern its type [systemic light chain amyloidosis (AL) vs transthyretin amyloidosis (ATTR)] using the pooled standardized mean difference (SMD). RESULTS: In total, six eligible studies with a total of 98 subjects were included in this meta-analysis. The pooled sensitivity was 0.95, the specificity was 0.98, positive LR was 10.130, negative LR was 0.1, and DOR was 148.83. The semiquantitative parameters of amyloid PET showed significantly higher values for cardiac amyloidosis patients than those for controls (pooled SMD = 1.42; P < .001), and in AL than ATTR (pooled SMD = 0.96; P < .001). CONCLUSION: Amyloid PET imaging can be a useful method for diagnosing cardiac amyloidosis. The semiquantitative parameters of amyloid PET can help diagnose cardiac amyloidosis and discern its type.

Prediction of breast cancer recurrence using lymph node metabolic and volumetric parameters from 18F-FDG PET/CT in operable triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer has a poor prognosis. We evaluated several metabolic and volumetric parameters from preoperative 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in the prognosis of triple-negative breast cancer and compared them with current clinicopathologic parameters. METHODS: A total of 228 patients with triple-negative breast cancer (mean age 47.0 ± 10.8 years, all women) who had undergone preoperative PET/CT were included. The PET/CT metabolic parameters evaluated included maximum, peak, and mean standardized uptake values (SUVmax, SUVpeak, and SUVmean, respectively). The volumetric parameters evaluated included metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Metabolic and volumetric parameters were evaluated separately for tumor (T) and lymph nodes (N). The prognostic value of these parameters was compared with that of clinicopathologic parameters. RESULTS: All lymph node metabolic and volumetric parameters showed significant differences between patients with and without recurrence. However, tumor metabolic and volumetric parameters showed no significant differences. In a univariate survival analysis, all lymph node metabolic and volumetric parameters (SUVmax-N, SUVpeak-N, SUVmean-N, MTV-N, and TLG-N; all P < 0.001), T stage (P = 0.010), N stage (P < 0.001), and TNM stage (P < 0.001) were significant parameters. In a multivariate survival analysis, SUVmax-N (P = 0.005), MTV (P = 0.008), and TLG (P = 0.006) with TNM stage (all P < 0.001) were significant parameters. CONCLUSIONS: Lymph node metabolic and volumetric parameters were significant predictors of recurrence in patients with triple-negative breast cancer after surgery. Lymph node metabolic and volumetric parameters were useful parameters for evaluating prognosis in patients with triple-negative breast cancer by 18F-FDG PET/CT, rather than tumor parameters.

Heterogeneity index evaluated by slope of linear regression on 18F-FDG PET/CT as a prognostic marker for predicting tumor recurrence in pancreatic ductal adenocarcinoma.

PURPOSE: 18F-Fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) has been investigated as a method to predict pancreatic cancer recurrence after pancreatic surgery. We evaluated the recently introduced heterogeneity indices of 18F-FDG PET/CT used for predicting pancreatic cancer recurrence after surgery and compared them with current clinicopathologic and 18F-FDG PET/CT parameters. METHODS: A total of 93 pancreatic ductal adenocarcinoma patients (M:F = 60:33, mean age = 64.2 ± 9.1 years) who underwent preoperative 18F-FDG PET/CT following pancreatic surgery were retrospectively enrolled. The standardized uptake values (SUVs) and tumor-to-background ratios (TBR) were measured on each 18F-FDG PET/CT, as metabolic parameters. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were examined as volumetric parameters. The coefficient of variance (heterogeneity index-1; SUVmean divided by the standard deviation) and linear regression slopes (heterogeneity index-2) of the MTV, according to SUV thresholds of 2.0, 2.5 and 3.0, were evaluated as heterogeneity indices. Predictive values of clinicopathologic and 18F-FDG PET/CT parameters and heterogeneity indices were compared in terms of pancreatic cancer recurrence. RESULTS: Seventy patients (75.3%) showed recurrence after pancreatic cancer surgery (mean recurrence = 9.4 ± 8.4 months). Comparing the recurrence and no recurrence patients, all of the 18F-FDG PET/CT parameters and heterogeneity indices demonstrated significant differences. In univariate Cox-regression analyses, MTV (P = 0.013), TLG (P = 0.007), and heterogeneity index-2 (P = 0.027) were significant. Among the clinicopathologic parameters, CA19-9 (P = 0.025) and venous invasion (P = 0.002) were selected as significant parameters. In multivariate Cox-regression analyses, MTV (P = 0.005), TLG (P = 0.004), and heterogeneity index-2 (P = 0.016) with venous invasion (P < 0.001, 0.001, and 0.001, respectively) demonstrated significant results. CONCLUSIONS: The heterogeneity index obtained using the linear regression slope, could be an effective predictor of pancreatic cancer recurrence after pancreatic cancer surgery, in addition to 18F-FDG PET/CT volumetric parameters and clinicopathologic parameters.

Evaluation of Data Entry Errors and Data Changes to an Electronic Data Capture Clinical Trial Database.

Monitoring of clinical trials includes several disciplines, stakeholders, and skill sets. The aim of the present study was to identify database changes and data entry errors to an electronic data capture (EDC) clinical trial database, and to access the impact of the changes. To accomblish the aim, Target e*CRF was used as the EDC tool for a multinational, dose-finding, multicenter, double-blind, randomized, parallel, placebo-controlled trial to investigate efficacy and safety of a new treatment in men with lower urinary tract symptoms associated with benign prostatic hyperplasia. The main errors observed were simple transcription errors from the paper source documents to the EDC database. This observation was to be expected, since every transaction has an inherant error rate. What and how to monitor must be assessed within the risk-based monitoring section of the comprehensive data monitoring plan. With the advent of direct data entry, and the elimination of the requirement to transcribe from a paper source record to an EDC system, error rates should go down dramatically. In addition, protocol violations and data outside the normal range can be identified at the time of data entry and not days, weeks, and months after the fact.

Therapeutic Responses and Survival Effects of 177Lu-PSMA-617 Radioligand Therapy in Metastatic Castrate-Resistant Prostate Cancer: A Meta-analysis.

PURPOSE: We performed a meta-analysis on the therapeutic effects of prostate-specific membrane antigen (PSMA)-617 labeled with lutetium-177 (Lu-PSMA-617) in patients with metastatic castration-resistant prostate cancer (mCRPC). PATIENTS AND METHODS: The primary outcome was the therapeutic responses after the first cycle of Lu-PSMA-617 radioligand therapy. The parameters studied were the pooled proportions of any prostate-specific antigen (PSA) decline and a greater than 50% PSA decline. The secondary outcome was the survival effects after Lu-PSMA-617 radioligand therapy. Studied parameters were pooled hazard ratios of the overall survival according to any PSA decline and a greater than 50% PSA decline after the first cycle of Lu-PSMA-617 radioligand therapy. RESULTS: In total, 10 eligible studies with 455 patients were finally included in this meta-analysis. The pooled proportions of any PSA decline was 68.00% (95% confidence interval [CI], 63.55%-72.22%], and those with a greater than 50% PSA decline was 34.45% (95% CI, 30.14%-38.97%). The pooled hazard ratios for the overall survival of any PSA decline was 0.29 (95% CI, 0.21-0.40) with significance (P < 0.00001); however, a greater than 50% PSA decline was 0.82 (95% CI, 0.54-1.25) with no significance (P = 0.39). CONCLUSIONS: We suggest that approximately two-thirds of any PSA decline and one-third of a greater than 50% PSA decline can be expected after the first cycle of Lu-PSMA-617 radioligand therapy in patients with mCRPC. Moreover, any PSA decline showed survival prolongation after the first cycle of the Lu-PSMA-617 radioligand therapy.

Extended Risk-Based Monitoring Model, On-Demand Query-Driven Source Data Verification, and Their Economic Impact on Clinical Trial Operations.

BACKGROUND: Computer-aided data validation enhanced by centralized monitoring algorithms is a more powerful tool for data cleaning compared to manual source document verification (SDV). This fact led to the growing popularity of risk-based monitoring (RBM) coupled with reduced SDV and centralized statistical surveillance. Since RBM models are new and immature, there is a lack of consensus on practical implementation. Existing RBM models' weaknesses include (1) mixing data monitoring and site process monitoring (ie, micro vs macro level), making it more complex, obscure, and less practical; and (2) artificial separation of RBM from data cleaning leading to resource overutilization. The authors view SDV as an essential part (and extension) of the data-validation process. METHODS: This report offers an efficient and scientifically grounded model for SDV. The innovative component of this model is in making SDV ultimately a part of the query management process. Cost savings from reduced SDV are estimated using a proprietary budget simulation tool with percent cost reductions presented for four study sizes in four therapeutic areas. RESULTS: It has been shown that an "on-demand" (query-driven) SDV model implemented in clinical trial monitoring could result in cost savings from 3% to 14% for smaller studies to 25% to 35% or more for large studies. CONCLUSIONS: (1) High-risk sites (identified via analytics) do not necessarily require a higher percent SDV. While high-risk sites require additional resources to assess and mitigate risks, in many cases these resources are likely to be allocated to non-SDV activities such as GCP, training, etc. (2) It is not necessary to combine SDV with the GCP compliance monitoring. Data validation and query management must be at the heart of SDV as it makes the RBM system more effective and efficient. Thus, focusing SDV effort on queries is a promising strategy. (3) Study size effect must be considered in designing the monitoring plan since the law of diminishing returns dictates focusing SDV on "high-value" data points. Relatively lower impact of individual errors on the study results leads to realization that larger studies require less data cleaning, and most data (including most critical data points) do not require SDV. Subsequently, the most significant economy is expected in larger studies.

Risk-Based Monitoring: A Closer Statistical Look at Source Document Verification, Queries, Study Size Effects, and Data Quality.

BACKGROUND: Data quality within the clinical research enterprise can be defined as the absence of errors that matter and whether the data are fit for purpose. This concept, proposed by the Clinical Trials Transformation Initiative, resulted from a culmination of collaboration with industry, academia, patient advocates, and regulators, and it emphasizes the presence of a hierarchy of error types, resulting in a more efficient and modern data-cleaning paradigm. While source document verification (SDV) is commonly used as a quality control method in clinical research, it is disproportionately expensive and often leads to questionable benefits. Although the current literature suggests that there is a need to reduce the burden of SDV, there is no consensus on how to replace this "tried and true" practice. METHODS: This article proposes a practical risk-based monitoring approach based on published statistical evidence addressing the impact of database changes subsequent to SDV. RESULTS: The analysis clearly demonstrates minimal effects of errors and error corrections on study results and study conclusions, with diminishing effect as the study size increases, and it suggests that, on average, <8% SDV is adequate to ensure data quality, with perhaps higher SDV rates for smaller studies and virtually 0% SDV for large studies. CONCLUSIONS: It is recommended that SDV, rather than just focusing on key primary efficacy and safety outcomes, focus on data clarification queries as highly discrepant (and the riskiest) data.

Impact of nocturia on health-related quality of life and medical outcomes study sleep score in men.

PURPOSE: To evaluate the impact of nocturia on health-related quality of life and sleep in men. METHODS: From January 2008 to December 2008, 284 patients with lower urinary tract symptoms were selected for this study. The participants completed a series of questionnaires on health-related quality of life (the overactive bladder questionnaire, or OAB-q), the Medical Outcomes Study (MOS) sleep scale, and the frequency volume chart. RESULTS: The patient population had a mean age of 60.0±13.4 years (range, 40 to 79 years). The mean duration of symptoms was 28.8±34.6 months. The mean number of voiding episodes per night was measured as follows: 88 patients (31.0%) reported no nocturia, 60 patients (21.1%) reported 2>voids/night ≥1, 56 patients (19.7%) reported 3>voids/night ≥2, and 80 patients (28.2%) reported ≥3 voids/night. The mean number of nocturia episodes increased with age (P=0.001), and the number of nocturia episodes was significantly associated with the OAB-q symptom score (P=0.001) and symptom bother (P=0.001). Among the categories of the MOS sleep scale, sleep index I (P=0.020), sleep disturbance (P=0.010), adequacy of sleep (P=0.005), and somnolence (P=0.041) were significantly associated with an increased number of nocturia episodes. CONCLUSIONS: The number of nocturia episodes increased with age in men. Nocturia appeared to be associated with further negative effects on sleep quality, health-related quality of life, and symptom bother.