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Combining biomarkers to optimize patient treatment recommendations.

ABSTRACT: Markers that predict treatment effect have the potential to improve patient outcomes. For example, the OncotypeDX® RecurrenceScore® has some ability to predict the benefit of adjuvant chemotherapy over and above hormone therapy for the treatment of estrogen-receptor-positive breast cancer, facilitating the provision of chemotherapy to women most likely to benefit from it. Given that the score was originally developed for predicting outcome given hormone therapy alone, it is of interest to develop alternative combinations of the genes comprising the score that are optimized for treatment selection. However, most methodology for combining markers is useful when predicting outcome under a single treatment. We propose a method for combining markers for treatment selection which requires modeling the treatment effect as a function of markers. Multiple models of treatment effect are fit iteratively by upweighting or "boosting" subjects potentially misclassified according to treatment benefit at the previous stage. The boosting approach is compared to existing methods in a simulation study based on the change in expected outcome under marker-based treatment. The approach improves upon methods in some settings and has comparable performance in others. Our simulation study also provides insights as to the relative merits of the existing methods. Application of the boosting approach to the breast cancer data, using scaled versions of the original markers, produces marker combinations that may have improved performance for treatment selection.

SUBMITTER: Kang C

PROVIDER: S-EPMC4248022 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Combining biomarkers to optimize patient treatment recommendations.

Kang Chaeryon C Janes Holly H Huang Ying Y

Biometrics 20140530 3

Markers that predict treatment effect have the potential to improve patient outcomes. For example, the OncotypeDX® RecurrenceScore® has some ability to predict the benefit of adjuvant chemotherapy over and above hormone therapy for the treatment of estrogen-receptor-positive breast cancer, facilitating the provision of chemotherapy to women most likely to benefit from it. Given that the score was originally developed for predicting outcome given hormone therapy alone, it is of interest to develo ...[more]

PMID: 24889663

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Project description:BACKGROUND:Convalescence advice is often based on tradition and anecdote from health care providers, rather than being based on experiences from patients themselves. The aim of this study was to analyse recovery in terms of resumption of various daily activities including work, following different laparoscopic and abdominal surgery in order to optimize an expert-based guideline on convalescence recommendations. METHODS:This is a prospective cohort study conducted in nine general and one university hospital in the Netherlands. Women aged 18-65 years and scheduled for a hysterectomy (laparoscopic, vaginal, abdominal) and/or laparoscopic adnexal surgery (n?=?304) were eligible to participate. Preoperatively, participants were provided with tailored expert-based convalescence recommendations on the graded resumption of several daily activities including sitting, standing, walking, climbing stairs, bending, lifting, driving, cycling, household chores, sport activities and return to work (RTW). Postoperatively, time until the resumption of these activities was tracked. Convalescence recommendations were considered correct when at least 25% and less than 50% of the women were able to resume an activity before or at the recommended recovery time. RESULTS:There was a wide variation in the duration until the resumption of daily activities within and between groups of patients undergoing different types of surgery. Recovery times lengthened with increasing levels of physical burden as well as with increasing levels of invasiveness of the surgery. For the majority of activities actual recovery times exceeded the recovery time recommended by the expert panel. CONCLUSIONS:This study provided insight in the resumption of daily activities after gynecological surgery and the adequacy of an expert-based convalescence guideline in clinical practice. Patient data was used to optimize the convalescence recommendations. TRIAL REGISTRATION:Dutch trial registry, NTR2087 (August 2009) and NTR2933 (June 2011).

Project description:PurposeIn some patients with Hodgkin lymphoma (HL), proton beam therapy (PBT) may reduce the risk of radiation-related cardiovascular disease (CVD) and second cancers (SC) compared with photon radiation therapy (RT). Our aim was to identify patients who benefit the most from PBT in terms of predicted 30-year absolute mortality risks (AMR30) from CVD and SC, taking into account individual background, chemotherapy, radiation, and smoking-related risks.Methods and materialsEighty patients with supradiaphragmatic HL treated with PBT between 2015 and 2019 were replanned using optimal photon RT. To identify patients predicted to derive the greatest benefit from PBT compared with photon RT, doses and AMR30 from CVD and SC of the lung, breast, and esophagus were compared for all patients and across patient subgroups.ResultsFor patients with mediastinal disease below the origin of the left main coronary artery (n = 66; 82%), PBT reduced the mean dose to the heart, left ventricle, and heart valves by 1.0, 2.7, and 3.6 Gy, respectively. Based on U.S. mortality rates, PBT reduced CVD AMR30 by 0.2%, from 5.9% to 5.7%. The benefit was larger if the mediastinal disease overlapped longitudinally with the heart by ≥40% (n = 23; 29%). PBT reduced the mean dose to the heart, left ventricle, and heart valves by 3.2, 5.6, and 5.1 Gy, respectively, and reduced CVD AMR30 by 0.8%, from 7.0% to 6.2%. For patients with axillary disease (n = 25; 31%), PBT reduced the mean lung dose by 2.8 Gy and lung cancer AMR30 by 0.6%, from 2.7% to 2.1%. Breast and esophageal doses were also lower with PBT, but the effects on AMR30 were negligible. The effect of smoking on CVD and lung cancer AMR30 was much larger than radiation and chemotherapy and the differences between radiation modalities.ConclusionsThe predicted benefit of PBT is not universal and limited to certain categories of patients with lymphoma and lower mediastinal or axillary disease. Smoking cessation should be strongly encouraged in smokers who require thoracic RT.

Project description:BackgroundSepsis is the most common trigger for AKI and up to 40% of mild or moderate septic AKI would progress to more severe AKI, which is associated with significantly increased risk for death and later CKD/ESRD. Early identifying high risk patients for AKI progression is a major challenge in patients with septic AKI.MethodsThis is a prospective, multicenter cohort study which enrolled adult patients with sepsis and initially developed stage 1 or 2 AKI in the intensive care unit from January 2014 to March 2018. AKI was diagnosed and staged according to 2012 KDIGO-AKI guidelines. Renal cell arrest biomarkers (urinary TIMP2*IGFBP7, u[TIMP-2]*[IGFBP7]) and renal damage biomarkers (urinary KIM-1[uKIM-1] and urinary IL-18 [uIL-18]) were measured at time of AKI clinical diagnosis, and the performance of biomarkers for predicting septic AKI progression alone or in combination were evaluated. The primary outcome was AKI progression defined as worsening of AKI stage. The secondary outcome was AKI progression with subsequent death during hospitalization.ResultsAmong 433 screened patients, 149 patients with sepsis and stage 1 or 2 AKI were included, in which 63 patients developed progressive AKI and 49 patients subsequently died during hospitalization. u[TIMP-2]*[IGFBP7], uKIM-1 and uIL-18 independently predicted the progression of septic AKI in which u[TIMP-2]*[IGFBP7] showed the greatest AUC (0.745; 95%CI, 0.667-0.823) as compared to uKIM-1 (AUC 0.719; 95%CI 0.638-0.800) and uIL-18 (AUC 0.619; 95%CI 0.525-0.731). Combination of u[TIMP-2]*[IGFBP7] with uKIM-1 improved the performance of predicting septic AKI progression with AUC of 0.752. u[TIMP-2]*[IGFBP7], alone or combined with uKIM-1/uIL-18, improved the risk reclassification over the clinical risk factor model alone both for the primary and secondary outcomes, as evidenced by significant category-free net reclassification index.ConclusionsCombination of renal cell arrest and damage biomarkers enhanced the prediction of AKI progression in patients with sepsis and improved risk reclassification over the clinical risk factors.

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Combining biomarkers to optimize patient treatment recommendations.

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Combining biomarkers to optimize patient treatment recommendations.

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