A spatial neighborhood methodology for computing and analyzing lymph node carcinoma similarity in precision medicine.

Precision medicine seeks to tailor therapy to the individual patient, based on statistical correlates from patients who are similar to the one under consideration. These correlates can and should go beyond genetics, and in general, beyond tabular or array data that can be easily represented computationally and compared. For example, in many types of cancer, cancer treatment and toxicity depend in large measure on the spatial disease spread-e.g., metastasizes to regional lymph nodes in head and neck cancer. However, there is currently a lack of methodology for integrating spatial information when considering patient similarity. We present a novel modeling methodology for the comparison of cancer patients within a cohort, based on the spatial spread of the lymph nodes affected in each patient. The method uses a topological map, bigrams, and hierarchical clustering to group patients based on their similarity. We compare this approach against a nonspatial (categorical) similarity approach where patients are binned solely by their affected nodes. We present similarity results on a 582 head and neck cancer patient cohort, along with two visual abstractions for analysis of the results, and we present clinician feedback. Our novel methodology partitions a patient cohort into clinically meaningful groups more susceptible to treatment side-effects. Such spatially-aware similarity approaches can help maximize the effectiveness of each patient's treatment.

Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration.

We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.

Renal Consequences of Diabetes After Kidney Donation.

Whether diabetes after kidney donation is associated with an accelerated GFR decay in the remaining kidney has not been studied. We determined the incidence of diabetes in kidney donors, and compared GFR change over time in diabetic to nondiabetic donors, in addition to the effect of diabetes mellitus (DM) on the development of proteinuria, hypertension, and end-stage renal disease (ESRD). Of the 4014 donors, 309 (7.7%) developed diabetes at a median age of 56.0 years and after a median of 18 years after donation. The difference in annual estimated GFR (eGFR) change between diabetic and nondiabetic donors in the 7 years before the development of DM was -0.08 mL/min/year; p = 0.51. After DM development, the difference was -1.10 mL/min/year for diabetic donors with hypertension and proteinuria, p < 0.001; -0.19 for diabetic donors with hypertension but no proteinuria, p = 0.29; -0.75 mL/min/year for diabetic donors with proteinuria but no hypertension, p = 0.19; and -0.09 mL/min/year for diabetic donors without proteinuria or hypertension, p = 0.63. When DM was considered as a time-dependent covariate, it was associated with the development of proteinuria (hazard ratio [HR] 2.65, 95% confidence interval [CI] 1.89-3.70; p < 0.001) and hypertension (HR 2.19, 95% CI 1.74-2.75; p < 0.001). It was not, however, associated with ESRD. eGFR decline after DM development exceeds that of nondiabetic donors only in diabetic donors with concomitant proteinuria and hypertension.

Defining the Tipping Point in Surgical Performance for Laparoscopic Donor Nephrectomy Among Transplant Surgery Fellows: A Risk-Adjusted Cumulative Summation Learning Curve Analysis.

The United Network for Organ Sharing recommends that fellowship-trained surgeons participate in 15 laparoscopic donor nephrectomy (LDN) procedures to be considered proficient. The American Society of Transplant Surgeons (ASTS) mandates 12 LDNs during an abdominal transplant surgery fellowship. We performed a retrospective intraoperative case analysis to create a risk-adjusted cumulative summation (RACUSUM) model to assess the learning curve of novice transplant surgery fellows (TSFs). Between January 2000 and December 2014, 30 novice TSFs participated in the organ procurement rotation of our ASTS-approved abdominal transplant surgery fellowship. Measures of surgical performance included intraoperative time, estimated blood loss, and incidence of intraoperative complications. The performance of senior TSFs was used to benchmark novice TSF performance. Scores were tabulated in a learning curve model, adjusting for case complexity and prior TSF case volume. Rates of adverse surgical events were significantly higher for novice TSFs than for senior TSFs. In univariable analysis, multiple renal arteries, high BMI, prior abdominal surgery, male donor, and nephrolithiasis were correlated with higher incidence of adverse surgical events. Based on the RACUSUM model, high intraoperative time is mitigated after 28 procedures, incidence of intraoperative complications tends to diminish after 24 procedures, and improvement in estimated blood loss did not remain consistent. TSFs exhibit a tipping point in LDN performance by 24-28 cases and proficiency by 35-38 cases.

Inosine triphosphatase deficiency helps predict anaemia, anaemia management and response in chronic hepatitis C therapy.

Anaemia frequently complicates peginterferon/ribavirin therapy for chronic hepatitis C infection. Better prediction of anaemia, ribavirin dose reduction or erythropoietin (EPO) need, may enhance patient management. Inosine triphosphatase (ITPA) genetic variants are associated with ribavirin-induced anaemia and dose reduction; however, their impact in real-life clinic patient cohorts remains to be defined. We studied 193 clinic patients with chronic hepatitis C infection of mixed viral genotype (genotype 1/4 n = 123, genotype 2/3, n = 70) treated with peginterferon/ribavirin. Patients were genotyped for ITPA polymorphisms rs1127354 and rs7270101 using Taqman primers. Hardy-Weinberg equilibrium was present. Estimated ITPA deficiency was graded on severity (0-3, no deficiency/mild/moderate/severe, n = 126/40/24/3, respectively). Multivariable models tested the association with anaemia at 4 weeks of treatment [including decline in haemoglobin (g/dL); haemoglobin <10 g/dL and haemoglobin decline >3 g/dL]; ribavirin dose reduction and EPO use and explored sustained viral response (SVR) to peginterferon/ribavirin. More severe ITPA deficiency was associated with less reduction in haemoglobin level (P <0.001; R(2) = 0.34), less ribavirin dose reduction (OR 0.42; (95% CI = 0.23-0.77); P = 0.005) and less EPO use [OR 0.53; (0.30-0.94); P = 0.029]. ITPA deficiency was associated with SVR [OR: 1.70; (1.02-2.83); P = 0.041] independently of clinical covariates (adjusted R(2) = 0.31). In this clinical cohort, ITPA deficiency helped predict the risk of on-treatment anaemia, ribavirin dose reduction, need for EPO support and was associated with SVR. For patients on HCV regimens including peginterferon/ribavirin, testing for ITPA deficiency may have clinical utility.

Interleukin 28B polymorphisms are the only common genetic variants associated with low-density lipoprotein cholesterol (LDL-C) in genotype-1 chronic hepatitis C and determine the association between LDL-C and treatment response.

Low-density lipoprotein cholesterol (LDL-C) levels and interleukin 28B (IL28B) polymorphism are associated with sustained viral response (SVR) to peginterferon/ribavirin (pegIFN/RBV) for chronic hepatitis C (CHC) infection. IL28B has been linked with LDL-C levels using a candidate gene approach, but it is not known whether other genetic variants are associated with LDL-C, nor how these factors definitively affect SVR. We assessed genetic predictors of serum lipid and triglyceride levels in 1604 patients with genotype 1 (G1) chronic hepatitis C virus (HCV) infection by genome-wide association study and developed multivariable predictive models of SVR. IL28B polymorphisms were the only common genetic variants associated with pretreatment LDL-C level in Caucasians (rs12980275, P = 4.7 × 10(-17), poor response IL28B variants associated with lower LDL-C). The association was dependent on HCV infection, IL28B genotype was no longer associated with LDL-C in SVR patients after treatment, while the association remained significant in non-SVR patients (P < 0.001). LDL-C was significantly associated with SVR for heterozygous IL28B genotype patients (P < 0.001) but not for homozygous genotypes. SVR modelling suggested that IL28B heterozygotes with LDL-C > 130 mg/dL and HCV RNA ≤600 000 IU/mL may anticipate cure rates >80%, while the absence of these two criteria was associated with an SVR rate of <35%. IL28B polymorphisms are the only common genetic variants associated with pretreatment LDL-C in G1-HCV. LDL-C remains significantly associated with SVR for heterozygous IL28B genotype patients, where LDL-C and HCV RNA burden may identify those patients with high or low likelihood of cure with pegIFN/RBV therapy.