A utility approach to individualized optimal dose selection using biomarkers

In many settings, including oncology, increasing the dose of treatment results in both increased efficacy and toxicity. With the increasing availability of validated biomarkers and prediction models, there is the potential for individualized dosing based on patient specific factors. We consider the setting where there is an existing dataset of patients treated with heterogenous doses and including binary efficacy and toxicity outcomes and patient factors such as clinical features and biomarkers. The goal is to analyze the data to estimate an optimal dose for each (future) patient based on their clinical features and biomarkers. We propose an optimal individualized dose finding rule by maximizing utility functions for individual patients while limiting the rate of toxicity. The utility is defined as a weighted combination of efficacy and toxicity probabilities. This approach maximizes overall efficacy at a prespecified constraint on overall toxicity. We model the binary efficacy and toxicity outcomes using logistic regression with dose, biomarkers and dose–biomarker interactions. To incorporate the large number of potential parameters, we use the LASSO method. We additionally constrain the dose effect to be non‐negative for both efficacy and toxicity for all patients. Simulation studies show that the utility approach combined with any of the modeling methods can improve efficacy without increasing toxicity relative to fixed dosing. The proposed methods are illustrated using a dataset of patients with lung cancer treated with radiation therapy.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154301/1/bimj2068.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154301/2/bimj2068_am.pd

The predictive role of soluble programmed death ligand 1 in digestive system cancers

IntroductionThe prognostic role of soluble programmed death ligand 1 (sPD-L1) in digestive system cancers (DSCs) remains inconclusive. This study aimed to explore the predictive value of sPD-L1 expression in DSCs.MethodsComprehensive searches were run on the electronic databases (PubMed, Web of Science, EMBASE, and the Cochrane Library) to identify studies that assessed the prognostic role of sPD-L1 in DSCs. Review Manager software (version 5.3) was used for all analyses. Pooled data for survival outcomes were measured as hazard ratios (HRs), 95% confidence intervals (CIs), and odds ratios and their 95% CIs.ResultsThe search identified 18 studies involving 2,070 patients with DSCs. The meta-outcome revealed that a high level of sPD-L1 was related to poorer overall survival (HR, 3.06; 95% CI: 2.22–4.22, p<0.001) and disease-free survival (HR, 2.53; 95% CI: 1.67–3.83, p<0.001) in DSCs. Individually, the prognostic significance of high level of sPD-L1 expression was the highest in hepatic cell carcinoma (HR, 4.76; p<0.001) followed by gastric cancer (HR=3.55, p<0.001).ConclusionsPD-L1 may be a prognostic factor in DSCs for overall survival and disease-free survival. Inflammatory cytokines, treatment approaches, and other factors may affect the expression of sPD-L1. Therefore, the prognostic value of sPD-L1 for recurrence and metastasis should be further investigated. sPD-L1 may also predict response to treatment. Well-designed prospective studies with standard assessment methods should be conducted to determine the prognostic value of sPD-L1 in DSCs

Modern Radiation Further Improves Survival in Non-Small Cell Lung Cancer: An Analysis of 288,670 Patients

Background: Radiation therapy plays an increasingly important role in the treatment of patients with non-small-cell lung cancer (NSCLC). The purpose of the present study is to assess the survival outcomes of radiotherapy treatment compared to other treatment modalities and to determine the potential role of advanced technologies in radiotherapy on improving survival. Methods: We used cancer incidence and survival data from the Surveillance, Epidemiology, and End Results database linked to U.S. Census data to compare survival outcomes of 288,670 patients with stage I-IV NSCLC treated between 1999 and 2008. The primary endpoint was overall survival. Results: Among the 288,670 patients diagnosed with stage I-IV NSCLC, 92,374 (32%) patients received radiotherapy-almost double the number receiving surgery (51,961, 18%). Compared to other treatment groups and across all stages of NSCLC, patients treated with radiotherapy showed greater median and overall survival than patients without radiation treatment (p < 0.0001). Radiotherapy had effectively improved overall survival regardless of age, gender, and histological categorization. Radiotherapy treatment received during the recent time period 2004 - 2008 is correlated with enhanced survival compared to the earlier time period 1999 - 2003. Conclusion: Radiation therapy was correlated with increased overall survival for all patients with primary NSCLC across stages. Combined surgery and radiotherapy treatment also correlates with improved survival, signaling the value of bimodal or multimodal treatments. Population-based increases in overall survival were seen in the recent time period, suggesting the potential role of advanced radiotherapeutic technologies in enhancing survival outcomes for lung cancer patients

Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non–Small Cell Lung Cancer

Purpose: Radiation pneumonitis is an important adverse event in patients with non–small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypothesized that inflammatory cytokines or the dynamic changes during radiotherapy can improve predictive accuracy for RP2. Experimental Design: Levels of 30 inflammatory cytokines and clinical information in patients with stages I–III NSCLC treated with radiotherapy were from our prospective studies. Statistical analysis was used to select predictive cytokine candidates and clinical covariates for adjustment. Machine learning algorithm was used to develop the generalized linear model for predicting risk RP2. Results: A total of 131 patients were eligible and 17 (13.0%) developed RP2. IL8 and CCL2 had significantly (Bonferroni) lower expression levels in patients with RP2 than without RP2. But none of the changes in cytokine levels during radiotherapy was significantly associated with RP2. The final predictive GLM model for RP2 was established, including IL8 and CCL2 at baseline level and two clinical variables. Nomogram was constructed based on the GLM model. The model's predicting ability was validated in the completely independent test set (AUC = 0.863, accuracy = 80.0%, sensitivity = 100%, specificity = 76.5%). Conclusions: By machine learning, this study has developed and validated a comprehensive model integrating inflammatory cytokines with clinical variables to predict RP2 before radiotherapy that provides an opportunity to guide clinicians

Monte Carlo-based lung cancer treatment planning incorporating PET-defined target volumes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135172/1/acm20065.pd

Impact of neoadjuvant chemotherapy on surgical outcomes among patients with hormone receptor positive breast cancer

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139969/1/jso24721.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139969/2/jso24721_am.pd

IDO Immune Status after Chemoradiation May Predict Survival in Lung Cancer Patients

Host immunity influences the impact of radiotherapy (RT) in cancer, but mechanistic connections remain obscure. In this study, we investigated the relationship of indoleamine 2,3-dioxygenase (IDO) systemic activity on clinical outcomes in RT-treated non-small cell lung cancer (NSCLC). IDO-mediated production of kynurenine and the kynurenine:tryptophan ratio in patient blood serum were determined for stage III NSCLC patients at times before, during, and after RT administration and then correlated to overall survival (OS), progression-free survival, and disease progression rate in patients. We found the impact of RT on these serum IDO markers to be heterogeneous in patients. On average, kynurenine:tryptophan ratios were reduced during RT but restored after RT. Notably, both baseline levels of kynurenine:tryptophan and changes in the levels of kynurenine after RT were significantly associated with OS. When combined, favorable change and favorable baseline corresponded with very long-term OS (median OS was not reached after 57 months of median follow-up). Favorable change combined with unfavorable baseline still corresponded with a lack of distant metastases. Our results suggest that RT alters IDO-mediated immune status in NSCLC patients and that changes in this serum biomarker may be useful to predict outcomes and perhaps personalize RT dosage to improve survival.Significance: Radiotherapy appears to influence systemic IDO activity and to exert a significant impact on metastatic risk and overall survival, with possible implications for defining a biomarker to optimize radiation dose in patients to improve outcomes. Cancer Res; 78(3); 809-16. ©2017 AACR

Thoracic radiation-induced pleural effusion and risk factors in patients with lung cancer

The risk factors and potential practice implications of radiation-induced pleural effusion (RIPE) are undefined. This study examined lung cancer patients treated with thoracic radiation therapy (TRT) having follow-up computed tomography (CT) or 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT. Increased volumes of pleural effusion after TRT without evidence of tumor progression was considered RIPE. Parameters of lung dose-volume histogram including percent volumes irradiated with 5-55 Gy (V5-V55) and mean lung dose (MLD) were analyzed by receiver operating characteristic analysis. Clinical and treatment-related risk factors were detected by univariate and multivariate analyses. 175 out of 806 patients receiving TRT with post-treatment imaging were included. 51 patients (24.9%) developed RIPE; 40 had symptomatic RIPE including chest pain (47.1%), cough (23.5%) and dyspnea (35.3%). Female (OR = 0.380, 95% CI: 0.156–0.926, p = 0.033) and Caucasian race (OR = 3.519, 95% CI: 1.327–9.336, p = 0.011) were significantly associated with lower risk of RIPE. Stage and concurrent chemotherapy had borderline significance (OR = 1.665, p = 0.069 and OR = 2.580, p = 0.080, respectively) for RIPE. Patients with RIPE had significantly higher whole lung V5-V40, V50 and MLD. V5 remained as a significant predictive factor for RIPE and symptomatic RIPE (p = 0.007 and 0.022) after adjusting for race, gender and histology. To include, the incidence of RIPE is notable. Whole lung V5 appeared to be the most significant independent risk factor for symptomatic RIPE

Doses of radiation to the pericardium, instead of heart, are significant for survival in patients with non-small cell lung cancer

Background and purpose: Higher cardiac dose was associated with worse overall survival in the RTOG0617 study. Pericardial effusion (PCE) is a common cardiac complication of thoracic radiation therapy (RT). We investigated whether doses of radiation to the heart and pericardium are associated with PCE and overall survival in patients treated with thoracic radiation for non-small cell lung cancer (NSCLC). Materials and Methods: A total of 94 patients with medically inoperable/unresectable NSCLC treated with definitive RT in prospective studies were reviewed for this secondary analysis. Heart and pericardium were contoured consistently according to the RTOG1106 Atlas, with the great vessels and thymus of the upper mediastinal structures included in the upper part of pericardium, only heart chambers included in the heart structure. Clinical factors and dose-volume parameters associated with PCE or survival were identified via Cox proportional hazards modeling. The risk of PCE and death were mapped using DVH atlases. Results: Median follow-up for surviving patients was 58 months. The overall rate of PCE was 40.4%. On multivariable analysis, dosimetric factors of heart and pericardium were significantly associated with the risk of PCE. Pericardial V30 and V55 were significantly correlated with overall survival, but presence of PCE and heart dosimetric factors were not. Conclusion: PCE was associated with both heart and pericardial doses. The significance of pericardial dosimetric parameters, but not heart chamber parameters, on survival suggests the potential significance of radiation damage to the cranial region of pericardium

Lon et al. Malaria Journal 2014, 13:96

Blackwater fever in an uncomplicated Plasmodium falciparum patient treated with dihydroartemisinin-piperaquin