Optimizing assessment of CD30 expression in Hodgkin lymphoma by controlling for low expression.

Since the approval of brentuximab vedotin (BV), assessment of CD30 status by immunohistochemistry gained increasing importance in the clinical management of patients diagnosed with CD30-expressing lymphomas, including classical Hodgkin lymphoma (CHL). Paradoxically, patients with low or no CD30 expression respond to BV. This discrepancy may be due to lack of standardization in CD30 staining methods. In this study, we examined 29 cases of CHL and 4 cases of nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) for CD30 expression using a staining protocol that was designed to detect low CD30 expression levels, and an evaluation system similar to the Allred scoring system used for breast cancer evaluation. For CHL, 10% of cases had low scores and 3% were CD30 negative, with 3 cases in which the majority of tumor cells showed very weak staining. Unexpectedly, one of four cases of NLPHL was positive. We demonstrate intra-patient heterogeneity in CD30 expression levels and staining patterns in tumor cells. Three CHL cases with weak staining may have been missed without the use of control tissue for low expression. Thus, standardization of CD30 immunohistochemical staining with use of known low-expressing controls may aid in proper CD30 assessment and subsequent therapeutic stratification of patients.

Pricing methods in outcome-based contracting: δ5: risk of efficacy failure-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The fifth dimension (δ5) estimates prices on the basis of the risk of efficacy failure of a drug. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: The risk of efficacy failure pricing dimension utilizes a seven-step method: (1) defining risk; (2) extracting data; (3) predicting models; (4) performing Monte Carlo Simulation (MCS) to estimate risk of efficacy failure; 5) estimating ranges for a payback; (6) adjusting for medical inflation; and (7) performing Monte Carlo Simulation (MCS) to estimate the DSPRisk of efficacy failure. A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). We estimated the risk of efficacy failure for osimertinib in terms of overall and progression-free survival versus standard of care. We used the estimated risk to estimate the price reduction on the wholesale acquisition cost (WAC) for the two hypothetical contracts: a 1-year (2019-2020) and 2-year contract (2019-2021). From this we estimated the DSPRisk of efficacy failure. RESULTS: Based on the risk of OS and PFS efficacy failure for osimertinib in OS and PFS, in the 1-year contract, the DSPRisk of efficacy failure was estimated at $12,652 (or -13.44% the 2018 WAC) for a 30-day prescription. For the 2-year contract (2019-2021), the DSPRisk of efficacy failure was estimated at $13,019 (or -10.93% the 2018 WAC). CONCLUSIONS: We demonstrated that pricing methods based on risk of efficacy failure methods can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Regularized continuous-time Markov Model via elastic net.

Continuous-time Markov models are commonly used to analyze longitudinal transitions between multiple disease states in panel data, where participants' disease states are only observed at multiple time points, and the exact state paths between observations are unknown. However, when covariate effects are incorporated and allowed to vary for different transitions, the number of potential parameters to estimate can become large even when the number of covariates is moderate, and traditional maximum likelihood estimation and subset model selection procedures can easily become unstable due to overfitting. We propose a novel regularized continuous-time Markov model with the elastic net penalty, which is capable of simultaneous variable selection and estimation for large number of parameters. We derive an efficient coordinate descent algorithm to solve the penalized optimization problem, which is fully automatic and data driven. We further consider an extension where one of the states is death, and time of death is exactly known but the state path leading to death is unknown. The proposed method is extensively evaluated in a simulation study, and demonstrated in an application to real-world data on airflow limitation state transitions.

Methods for peptide and protein quantitation by liquid chromatography-multiple reaction monitoring mass spectrometry.

Liquid chromatography-multiple reaction monitoring mass spectrometry of peptides using stable isotope dilution (SID) provides a powerful tool for targeted protein quantitation. However, the high cost of labeled peptide standards for SID poses an obstacle to multiple reaction monitoring studies. We compared SID to a labeled reference peptide (LRP) method, which uses a single labeled peptide as a reference standard for all measured peptides, and a label-free (LF) approach, in which quantitation is based on analysis of un-normalized peak areas for detected MRM transitions. We analyzed peptides from the Escherichia coli proteins alkaline phosphatase and ß-galactosidase spiked into lysates from human colon adenocarcinoma RKO cells. We also analyzed liquid chromatography-multiple reaction monitoring mass spectrometry data from a recently published interlaboratory study by the National Cancer Institute Clinical Proteomic Technology Assessment for Cancer network (Addona et al. (2009) Nat. Biotechnol. 27: 633-641), in which unlabeled and isotopically labeled synthetic peptides or their corresponding proteins were spiked into human plasma. SID displayed the highest correlation coefficients and lowest coefficient of variation in regression analyses of both peptide and protein spike studies. In protein spike experiments, median coefficient of variation values were about 10% for SID and 20-30% for LRP and LF methods. Power calculations indicated that differences in measurement error between the methods have much less impact on measured protein expression differences than biological variation. All three methods detected significant (p < 0.05) differential expression of three endogenous proteins in a test set of 10 pairs of human lung tumor and control tissues. Further, the LRP and LF methods both detected significant differences (p < 0.05) in levels of seven biomarker candidates between tumors and controls in the same set of lung tissue samples. The data indicate that the LRP and LF methods provide cost-effective alternatives to SID for many quantitative liquid chromatography-multiple reaction monitoring mass spectrometry applications.

Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry.

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.