Predictors Of Relapse In Patients Research Articles

Leishmania blood parasite dynamics during and after treatment of visceral leishmaniasis in Eastern Africa: A pharmacokinetic-pharmacodynamic model.

With the current treatment options for visceral leishmaniasis (VL), recrudescence of the parasite is seen in a proportion of patients. Understanding parasite dynamics is crucial to improving treatment efficacy and predicting patient relapse in cases of VL. This study aimed to characterize the kinetics of circulating Leishmania parasites in the blood, during and after different antileishmanial therapies, and to find predictors for clinical relapse of disease. Data from three clinical trials, in which Eastern African VL patients received various antileishmanial regimens, were combined in this study. Leishmania kinetoplast DNA was quantified in whole blood with real-time quantitative PCR (qPCR) before, during, and up to six months after treatment. An integrated population pharmacokinetic-pharmacodynamic model was developed using non-linear mixed effects modelling. Parasite proliferation was best described by an exponential growth model, with an in vivo parasite doubling time of 7.8 days (RSE 12%). Parasite killing by fexinidazole, liposomal amphotericin B, sodium stibogluconate, and miltefosine was best described by linear models directly relating drug concentrations to the parasite elimination rate. After treatment, parasite growth was assumed to be suppressed by the host immune system, described by an Emax model driven by the time after treatment. No predictors for the high variability in onset and magnitude of the immune response could be identified. Model-based individual predictions of blood parasite load on Day 28 and Day 56 after start of treatment were predictive for clinical relapse of disease. This semi-mechanistic pharmacokinetic-pharmacodynamic model adequately captured the blood parasite dynamics during and after treatment, and revealed that high blood parasite loads on Day 28 and Day 56 after start of treatment are an early indication for VL relapse, which could be a useful biomarker to assess treatment efficacy of a treatment regimen in a clinical trial setting.

Clinical, histological features, and predictors of relapse in patients with idiopathic granulomatous mastitis.

Idiopathic granulomatous mastitis is a benign, inflammatory disease of breasts characterized by non-caseating granulomas. Our study aims to identify distinguishing clinical and histopathological features of relapsing disease compared to those in complete remission. We queried databases at our institution (1990-2021) to include females ≥18 years with biopsy-proven diagnosis of idiopathic granulomatous mastitis, excluding patients with breast cancer, lymphoproliferative disorders, solid organ malignancy, foreign body reaction in breast, plasma cell mastitis, and ductal ectasia. Remission was defined as a 3-month period without recurrence of symptoms or imaging findings. Relapse was defined as recurrence after 3 months of remission. Clinical and histopathological features were compared using 2-sample t tests and chi-squared tests. Of the 27 patients that met our inclusion criteria, the mean age at diagnosis was 35.8 years (± standard deviation 9.4 years) with a mean body mass index of 31.7 kg/m2 (± standard deviation 6.7 kg/m2). 11 (41%) were Hispanic, 25 (93%) had at least one previous full-term pregnancy prior to diagnosis and 8 (30%) were on oral contraceptives. Remission was seen in 18 patients (66%) and 9 (33%) had relapse. Six of these patients received steroids after antibiotics, while 5 patients received methotrexate. Three (33%) patients with relapse and 14 (77%) with remission, had abscess formation confirmed on histopathology (P = .04). Patients with remission had a higher number of abscesses on histopathology and history of oral contraceptive use was associated with more relapse. By identifying key clinical and histopathological findings in this population may guide prognosis and treatment of these patients.

Personalized relapse prediction in patients with major depressive disorder using digital biomarkers

Major depressive disorder (MDD) is a chronic illness wherein relapses contribute to significant patient morbidity and mortality. Near-term prediction of relapses in MDD patients has the potential to improve outcomes by helping implement a ‘predict and preempt’ paradigm in clinical care. In this study, we developed a novel personalized (N-of-1) encoder-decoder anomaly detection-based framework of combining anomalies in multivariate actigraphy features (passive) as triggers to utilize an active concurrent self-reported symptomatology questionnaire (core symptoms of depression and anxiety) to predict near-term relapse in MDD. The framework was evaluated on two independent longitudinal observational trials, characterized by regular bimonthly (every other month) in-person clinical assessments, weekly self-reported symptom assessments, and continuous activity monitoring data with two different wearable sensors for ≥ 1 year or until the first relapse episode. This combined passive-active relapse prediction framework achieved a balanced accuracy of ≥ 71%, false alarm rate of ≤ 2.3 alarm/patient/year with a median relapse detection time of 2–3 weeks in advance of clinical onset in both studies. The study results suggest that the proposed personalized N-of-1 prediction framework is generalizable and can help predict a majority of MDD relapses in an actionable time frame with relatively low patient and provider burden.

Predictors of relapse in patients with oligoarticular juvenile idiopathic arthritis in remission off medication.

The aim of this study was to evaluate the predictors of relapse in patients with oligoarticular juvenile idiopathic arthritis (oJIA) who achieved clinical remission off medication. This retrospective observational study was conducted between June 2009 and July 2022 in 126 patients with oJIA who achieved remission off medication. The relationships between relapse status and demographic, clinical and laboratory findings, and treatment details were evaluated using electronic medical records. Of the 126 oJIA patients who achieved remission off medication, 85 (67.5%) were female. Relapse occurred in 31 patients (24.6%) with remission off medication after a median of 18months (IQR 7-26). No statistically significant relationship was found between gender, age at diagnosis, oJIA subtype, number of joints, ANA, ESR, CRP level, initial Juvenile Arthritis Disease Activity Score and relapse in oJIA patients who achieved remission off medication (p = 0.66, p = 0.25, p = 1, p = 0.54, p = 0.29, p = 0.59, p = 0.95 and p = 0.52, respectively). There was a statistically significant relationship between the number of intraarticular corticosteroid injections (IACIs) and relapse (p = 0.01). Patients who underwent IACI 2-3 times had more relapses than those who never underwent IACI and those who underwent IACI only once (p = 0.01, p = 0.02, respectively). A relationship was found between the length of follow-up and relapse in patients with oJIA who achieved remission off medication (p = 0.035). Conclusion: In oJIA patients who achieve remission off medication, the probability of relapse increases in patients who need ≥ 2 IACI during the period until remission. The length of follow-up period is associated with the probability of relapse. What is Known: • Approximately one-fourth of oJIA patients who are in remission off medication have relapse. • There is a need for markers that can predict the risk of relapse in oJIA patients who achieve remission on or off medication. What is New: • The possibility of relapse should be considered in patients with oJIA who need ≥ 2 IACIs until achieving remission off medication. • The relapse rate may increase as the follow-up period prolongs in patients who achieve remission off medication.

Postoperative Relapse Prediction in Patients With Ewing Sarcoma Using Computed Tomography-Based Radiomics Models Covering Tumor Per Se and Peritumoral Signatures.

We aimed to develop and validate a computed tomography (CT)-based radiomics model for early relapse prediction in patients with Ewing sarcoma (ES). We recruited 104 patients in this study. Tumor areas and areas with a tumor expansion of 3 mm were used as regions of interest for radiomics analysis. Six different models were constructed: Pre-CT, CT enhancement (CTE), Pre-CT +3 mm , CTE +3 mm , Pre-CT and CTE combined (ComB), and Pre-CT +3 mm and CTE +3 mm combined (ComB +3 mm ). All 3 classifiers used a grid search with 5-fold cross-validation to identify their optimal parameters, followed by repeat 5-fold cross-validation to evaluate the model performance based on these parameters. The average performance of the 5-fold cross-validation and the best one-fold performance of each model were evaluated. The AUC (area under the receiver operating characteristic curve) and accuracy were calculated to evaluate the models. The 6 radiomics models performed well in predicting relapse in patients with ES using the 3 classifiers; the ComB and ComB +3 mm models performed better than the other models (AUC -best : 0.820-0.922/0.823-0.833 and 0.799-0.873/0.759-0.880 in the training and validation cohorts, respectively). Although the Pre-CT +3 mm , CTE +3 mm, and ComB +3 mm models covering tumor per se and peritumoral CT features preoperatively forecasted ES relapse, the model was not significantly improved. The radiomics model performed well for early recurrence prediction in patients with ES, and the ComB and ComB +3 mm models may be superior to the other models.

Epidemiology and predictors of relapse in giant cell arteritis: A systematic review and meta-analysis.

The aim of this study was to estimate the timing of relapse, the prevalence of multiple relapses and the predictors of relapse in patients with giant cell arteritis (GCA). PubMed, Embase and Cochrane databases were searched from inception till November, 30 2021. Outcome measures include cumulative relapse rate (CRR) of first relapse at year 1, 2, and 5 after treatment initiation, CRR of second and third relapse and predictors of relapse. Thirty studies (2595 patients) were included for timing of relapse, 16 studies (1947 patients) for prevalence of multiple relapses and 40 studies (4213 patients) for predictors of relapse. One-year, 2-year and 5-year CRRs were 32% [95% confidence interval (CI) 22-43%], 44% [95% CI 31-59%], and 47% [95% CI 27-67%], respectively. The duration of scheduled glucocorticoid therapy was negatively associated with the 1-year CRR (P=0.03). CRR of second and third relapse were 30% [95% CI 21-40] and 17% [95% CI 8-33%], respectively. Female sex (OR 1.43) and large vessel involvement (OR 2.04) were predictors of relapse. Relapse occurred in almost half of GCA patients mainly during the first two years after diagnosis. One in three patients had multiple relapses. The optimal glucocorticoid tapering schedule, which seeks a balance between the lowest relapse risk and the shortest glucocorticoid duration, needs to be determined in future studies. Longer scheduled glucocorticoid therapy or early introduction of glucocorticoid-sparing agents may be warranted in female patients and patients with large vessel involvement.

Time-Dependent Prediction of Relapse in Patients with Acute Myeloid Leukemia

Background: Although most patients with newly diagnosed acute myeloid leukemia (AML) obtain a complete remission (CR) following induction chemotherapy, most subsequently relapse. Previous studies have demonstrated the importance of various prognostic factors for relapse-free survival, including age, cytogenetics, prior antecedent hematologic disorder (AHD), and prior cancer-related therapy. However, assessments of treatment response now include additional factors such as measurable residual disease (MRD) status, time to count recovery, and remission type (CR vs. CR with incomplete count recovery [CRi]). Among patients in complete remission, we set out to examine the impact of additional initial response variables on relapse or death at various time points up to 3 years, a time point after which AML relapses become very uncommon. Methods: Of 972 patients who had a confirmed diagnosis of AML or other high-grade myeloid neoplasm (≥10% blasts) underwent initial induction treatment at University of Washington / Fred Hutchinson Cancer Center between November 2008 and December 2018, 656 achieved a morphologic remission (CR or CRi) and were included in our analysis. The primary outcomes were survival without relapse after 1, 2, or 3 years. Multivariable logistic regression models controlled for the following covariates: age, ELN 2017 risk classification, presence of MRD determined by multiparameter flow cytometry at first remission, gender, WBC count at diagnosis, prior AHD and/or therapy-related disease, performance status, treatment-related mortality (TRM) score, induction intensity (high: CLAG-M, FLAG-ida, or similar; intermediate: 7+3 or similar; low: hypomethylating agent with or without venetoclax), CR vs CRi, and count recovery within 30 days. Time to relapse was estimated using relapse-free survival curves. Results: The median age at diagnosis was 60 years (range 18-91). De novo AML was found in 373 patients (57%) with the remainder a mix of antecedent AHD and therapy-related AML. ELN2017 risk classification was favorable in 181 patients (28%), intermediate in 206 (41%), and adverse in 203 (31%). Performance status was 0-1 in 538 patients (82%). Most patients received high or intermediate-intensity induction (88%). After induction, 540 patients (82%) achieved a CR and 116 patients (18%) CRi. MRD following induction therapy was found in 173 patients (26%). In multivariable analysis, age, remission type (CRi), and MRD status were the strongest predictors of being alive without relapse at years 1, 2, and 3 (year 3 summarized in Table 1). In the year 3 model, CR MRD+ after induction was associated with the largest decrease in odds of being alive without relapse (CR MRD+: odds ratio [OR] 0.15, 95% confidence interval [CI] 0.08-0.27). 3-year relapse-free survival (RFS) of 18.5% (95% CI 13.5-25.5%) for MRD+ patients versus 36.4% (95% CI 31.3-42.4%) for MRD- patients (Figure 1). CRi MRD+/MRD- were both also associated with decreased survival with CRi MRD- (OR 0.33, 95% CI 0.16-0.65) and CRi MRD+ (OR 0.40, 95% CI 0.18-0.87). Increasing age was the second strongest predictor across the models (year 3 OR 0.78, 95% CI 0.67-0.89). Conclusions: Our study identified remission category (CR vs CRi), MRD status, and age as the strongest predictors of being alive without relapse at years 1, 2, or year 3 following induction for patients with AML and other high-grade myeloid neoplasms. Patients with older age or those with evidence of residual detectable disease with MRD or CRi and/or MRD have an increased risk of relapse or death in the first 3 years after initial CR. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Cell-Free DNA (cfDNA)-Based Measurable Residual Disease (MRD) Detection As a Predictor of Relapse Post-Allogeneic Blood or Marrow Transplant (alloBMT) in Patients with Myeloid Malignancies

Background: AlloBMT is the only curative therapy for many patients with acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). With the significant improvement in non-relapse mortality, disease relapse remains the main cause of therapeutic failure. The presence of leukemia-specific somatic mutations provides an attractive strategy for molecular assessment of measurable residual disease (MRD). The level of MRD at the time of complete remission (CR) has been an important predictor of relapse in patients undergoing alloBMT. Widely utilized molecular MRD assays require invasive bone marrow (BM) aspiration to ensure an adequate amount of residual leukemia cells. Circulating tumor DNA (ctDNA) released from malignant cells can be reliably detected in patients' plasma and has been widely used in diagnosis, early detection, and disease burden monitoring in solid tumors. This assay is not widely used in myeloid malignancies as the proper assessment of its technical and clinical utility as an MRD monitoring strategy has not been performed. In the current study, we aimed to determine the differential sensitivity between bone marrow and ctDNA-based MRD and its utility as a minimally invasive diagnostic and disease monitoring tool. Additionally, we evaluated the clinical utility of dynamic ctDNA-based MRD monitoring and its effect on post-alloBMT relapse by using plasma samples from 2 large prospective clinical trials (BMT CTN 0201 and 0402). Methods: The technical validation cohort included 20 consecutive patients with myeloid malignancies undergoing alloBMT at Johns Hopkins. A minimum of 10mL of plasma and bone marrow DNA was collected at the time of remission and at multiple time points after alloBMT. The clinical validation cohort included 90 patients participating in two prospective alloBMT trials (BMT CTN-0201 and 0402). The eligibility criteria included the diagnosis of myeloid malignancy (72 AML, 18 MDS) and the minimum of 2mL of plasma available from day 0 and/or day 90 after alloBMT. Ultra-deep error-corrected targeted sequencing was performed on plasma and bone marrow-derived DNA. The variant allele frequency (VAF) per patient was represented by the maximum VAF of all detected mutations. Results: To measure the exact contribution of hematopoietic tissue to plasma cell-free DNA (cfDNA) we analyzed cfDNA in alloBMT recipients. Using donor and recipient-specific polymorphisms we demonstrated that after full donor hematopoietic reconstitution by standard chimerism assays (day +180), 94.6% (range 93.9-95.3%) of cfDNA was of hematopoietic origin. To determine the differential sensitivity of the cfDNA vs. BM-based MRD we focused only on leukemia-specific mutations found in the diagnostic specimens. The minimum level of detection was 0.03%. Forty leukemia-specific mutations were detected in the technical validation cohort. Out of 31 mutations seen in the BM, only 3 were not detected in cfDNA (3/31, 9.7%). On the contrary, out of 37 mutations in cfDNA, 9 were not seen in BM (9/37, 25%). While we observed a strong positive correlation (rho = 0.8, p<0.0001) at any level of MRD between BM and cfDNA, cfDNA was superior at the lower MRD level (VAF cut-off < 0.26%). The clinical utility of cfDNA MRD was utilized in a separate validation cohort of 90 patients enrolled on 2 BMT CTN trials. The median (Q1, Q3) follow-up was 26 months (25 - 27 months). cfDNA-MRD positivity (VAF cutoff >0.25%) at day +90 was associated with significantly worse relapse-free survival (RFS) (46.2% vs 84.0%, p<0.001) and overall survival (OS) at two years (53.8% vs 87.2%, p=0.0013) after alloBMT. Conclusions: cfDNA-based MRD assessment appears to be a promising, minimally invasive test that provides important prognostic information in patients with myeloid malignancies undergoing alloBMT. The presence of cfDNA MRD at day 90 post alloBMT was associated with significantly worse RFS and OS in patients with myeloid malignancies. The dynamic assessment of MRD by cfDNA may not only provide important prognostic information but may also guide the therapeutic decision-making and timely implementation of post-alloBMT maintenance therapies to improve outcomes of patients with myeloid malignancies. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

High Expressed Emotion (HEE), Assessed Using the Five-Minute Speech Sample (FMSS), as a Predictor of Psychiatric Relapse in Patients with Schizophrenia and Major Depressive Disorder: A Meta-Analysis and Meta-Regression.

Expressed Emotion (EE) describes the tone of a caregiver's response to a patient with a mental disorder, and it is used to predict relapse. The Five-Minute Speech Sample (FMSS) is a 5-min interview with a caregiver that evaluates only two EE dimensions. The present study aimed at evaluating HEE (High Expressed Emotion) as a predictor of relapse in patients with schizophrenia and major depressive disorder. Six studies were selected for the meta-analysis. In total, the studies included 297 subjects. The analyses included a random effects model; a meta-analysis excluding the study with the smallest sample; a cumulative meta-analysis; a meta-regression with random effects, using patient age and duration of illness as moderators; a leave-one-out meta-analysis; and a funnel plot to estimate publication bias. The FMSS emerged as a valid and reliable tool for measuring EE as a predictor of relapse in patients with schizophrenia and major depressive disorder. Patient age and duration of illness had no significant effect on the results. Future meta-analyses should include more studies to reduce publication bias. EE may be a good predictor of relapse when examined through a fast measurement technique such as the FMSS, which may also be useful to analyze the psychopathological structure of caregivers.

Increased monocyte abundance as a marker for relapse after discontinuation of biologics in inflammatory bowel disease with deep remission

Monocytes are involved in the upstream inflammatory process in the immune reaction in inflammatory bowel disease (IBD). Patients with IBD who discontinued biologics have been found to relapse, even after checking for deep remission. This study investigated whether monocytes could act as a predictor of relapse in patients who experienced relapse after the discontinuation of biologics. To this end, pediatric patients (<19 years old, n = 727) diagnosed with IBD from January 2003 to December 2021 were retrospectively reviewed. Clinical features, monocytes, and disease activity at the time of discontinuing biologics were evaluated by dividing patients into a relapsed group and a non-relapsed group after discontinuing biologics. The percentage of monocytes (8.65% vs. 6.42%, P < 0.001), the absolute monocyte count (614.79 cells/μL vs. 381.70 cells/μL, P < 0.001), and the monocyte/polymorphonuclear leukocyte (PMN) ratio (0.18 vs. 0.11, P < 0.001) at the time of discontinuation were significantly higher in patients who experienced relapse. As a result of multivariate analysis, the monocyte percentage (odds ratio: 2.012, P < 0.001) and monocyte/PMN ratio (odds ratio: 4.320E+14, P = 0.002) were evaluated as risk factors for relapse. Diagnostic capability was confirmed using area under operating characteristic curve (0.782) of the monocyte percentage for assessing the relapse within 6 months with cutoff value of 8.15% (P < 0.001). The findings presented in this study indicate that the patients with high monocyte counts experienced relapse after the discontinuation of biologics. A monocyte percentage of over 8.15% in theblood at the time of discontinuation was found to be associated with a high probability of relapse within 6 months, even in deep remission.

Predictors of relapse in granulomatosis with polyangiitis: a multi-center study

BackgroundGranulomatosis with polyangiitis (GPA) is a rare systemic vasculitis. Its severity ranges from indolent disease to fulminant that may cause death. With treatment, remission is seen in more than 80% of cases, although relapse is still common. There have been studies showing that there may be factors to predict relapse in GPA. Based on relapses, the decision to start treatment and/or to monitor the patients more closely is made. Therefore, predicting the relapse of GPA can be effective in controlling the disease. Our aim was to investigate possible factors for relapse in GPA.We recruited 254 patients diagnosed with GPA who were under treatment at Alzahra hospital affiliated to Isfahan University of Medical Sciences (from 2013 to 2020) and Amir Alam Hospital affiliated to Tehran University of Medical Sciences (from 2020 to 2022) to plan a retrospective study. Chi-squared or Fisher’s exact tests were performed to compare categorical variables, while the Mann–Whitney U test was used to compare continuous variables.ResultsAnalysis of our patients (aged 20–80,122 females) showed that 147 patients (57.9%) experienced relapse. Mean age in relapse group was 43.8 ± 16.6 and in no-relapse group was 45.6 ± 15.1 (P > 0.05). Among many potential predictors, we observed in multivariate analysis that positive PR3-ANCA (proteinase 3-antineutrophilic cytoplasmic antibodies) (P = 0.007, OR:2.62,CI:1.29–5.31),nose manifestations (P = 0.004, OR 3.00, CI 1.43–6.26), mucosal membranes involvement (P = 0.009, OR 4.21, CI 1.43–12.38), and gastrointestinal tract (GI) complications (P = 0.03, OR 5.64, CI 1.14–27.90) were significant predictors of GPA relapse.ConclusionAmong clinical and laboratory features we studied, positive PR3-ANCA, nose manifestations, mucosal membranes involvement, and GI complications were independent predictors of relapse in patients with GPA.

P382. Replication of Personalized Relapse Prediction in Patients With Major Depressive Disorder Using Digital Biomarkers

Relapses and recurrences contribute to the significant morbidity and mortality in Major Depressive Disorder (MDD). Recent advances in mobile technologies and wearable sensors have enabled continuous remote monitoring of patients with MDD. Here we discuss the replication results of personalized (N of 1) relapse prediction framework using actigraphy data and self-reported symptoms to predict relapse and recurrence in MDD.

Using a 31-Gene Expression Profile Test to Stratify Patients with Stage I-II Cutaneous Melanoma According to Recurrence Risk: Update to a Prospective, Multicenter Study.

Simple SummaryMany people with skin cancer will have their cancer come back. The 31-gene expression profile (31-GEP) test can help predict if a cancer has a low (Class 1) or high (Class 2) chance of returning. This study looked at 86 patients with early skin cancer to see how well the 31-GEP test predicted if their cancer would return. None of the patients with a Class 1 GEP result had their cancer return within 3 years, but one-fourth of patients with a Class 2 result did. This study showed that the 31-GEP test can help predict if a patient’s skin cancer will return. Accurate risk prediction can help doctors make better treatment plans for patients with skin cancer.Background: Fifteen to forty percent of patients with localized cutaneous melanoma (CM) (stages I–II) will experience disease relapse. The 31-gene expression profile (31-GEP) uses gene expression data from the primary tumor in conjunction with clinicopathologic features to refine patient prognosis. The study’s objective was to evaluate 31-GEP risk stratification for disease-free survival (DFS) in a previously published cohort with longer follow-up. Methods: Patients with stage IB–II CM (n = 86) were prospectively tested with the 31-GEP. Follow-up time increased from 2.2 to 3.9 years. Patient outcomes were compared using Kaplan-Meier and Cox regression analysis. Results: A Class 2B result was a significant predictor of 3-year DFS (hazard ratio (HR) 8.4, p = 0.008) in univariate analysis. The 31-GEP significantly stratified patients by risk of relapse (p = 0.005). A Class 2B result was associated with a lower 3-year DFS (75.0%) than a Class 1A result (100%). The 31-GEP had a high sensitivity (77.8%) and negative predictive value (95.0%). Conclusions: The 31-GEP is a significant predictor of disease relapse in patients with stage IB–II melanoma and accurately stratified patients by risk of relapse.

Tumor Budding as a Predictive Marker of Relapse and Survival in Patients With Stage II Colon Cancer.

Tumor budding (TB) has recently been recognized worldwide as a prognostic predictor in several solid cancers. The objective of this study was to explore the relationship between TB and clinicopathological characteristics, postoperative relapse, and survival in patients with stage II colon cancer. A total of 213 patients with stage II colon cancer were retrospectively enrolled at Saitama Medical Center, Dokkyo Medical University from 2010 to 2016. TB was evaluated in hotspot areas on hematoxylin and eosin-stained slides at the invasive front of the tumor to define a low-grade group (BD1) and a high-grade group (BD2 or BD3). High-grade TB was found in 38.3% of cases, and was associated with pT4, presence of lymphovascular invasion, and tumor relapse (p=0.02, p=0.03, p=0.002, respectively). Patients with highgrade TB showed worse relapse-free survival (RFS) and overall survival (OS) rates than patients with low-grade TB (5-year RFS: High 75.6% vs. Low 92.1%, p=0.001; 5-year OS: High 93.7% vs. Low 93.7%, p=0.001). On multivariate analysis for predictors of RFS and OS, high-grade TB was significant for both RFS and OS (RFS, p=0.003; OS, p=0.005). Patients with high-grade TB experienced lung and liver relapses significantly more frequently than patients with low-grade TB (p=0.03 each). Among patients who received adjuvant chemotherapy (AC), no patients showed lung or liver relapse even in the presence of high-grade TB. TB may offer a useful predictor of relapse in patients with stage II colon cancer after surgery, and AC should be considered for patients with high-grade TB.

Causes, frequencies, and predictors of relapse in patients with ulcerative colitis on long-term follow-up in a tertiary care hospital of Northern India

Context: Ulcerative colitis (UC) initially thought to be a disease of developed world is equally common in India. Surprisingly, there are very scant data from India. The study was undertaken to find the frequency of relapse and to determine factors predictor of relapse in Indian population. Subjects and Methods: This study was conducted at a tertiary care center of New Delhi for a period of 1 year. Patients were included if they had a diagnosis of UC based on accepted historical, endoscopic, histological, and/or radiologic criteria. Detailed past/present history, baseline clinical examination, dietary details, and psychological analysis using shortened Depression Anxiety Stress Scale score, biochemical tests, inflammatory markers, endoscopic, and histopathological analysis were done at baseline and regular intervals. The outcome was clinical relapse or continued remission. Results: Out of 86 patients screened, 50 patients were included in the study according to inclusion criteria and were followed up. The frequency of relapse was 32%. Univariate analysis showed higher relapse frequency, frequency of steroid received in past, patients on immunomodulator therapy, presence of acute or chronic inflammatory cells on histology, and disease activity at baseline as predictors of relapse. There was no significant difference between anxiety, stress, and depression relapsers and those who maintained remission. On multivariate analysis, disease activity at baseline was the only independent predictor of relapse. Conclusions: Stringent control of disease activity with mucosal healing should be the aim, as mucosal healing is the only predictor for prolonged remission.

Microhematuria Enhances the Risks of Relapse and Renal Progression in Primary Membranous Nephropathy.

Objective: To determine whether there is an association between microhematuria and relapse or kidney disease progression in patients with primary membranous nephropathy (PMN).Methods: A cohort of 639 patients with biopsy-proven PMN from two centers was followed for a median of 40 months. The exposures were initial hematuria, time-averaged hematuria, and cumulative duration of hematuria. The outcomes were relapse and renal progression, which were defined by a 40% reduction in renal function or end-stage renal disease. Cox proportional hazards regression and competing risk analyses were performed to yield hazard ratios (HRs) and subdistribution hazard ratios (sHRs) with 95% confidence intervals (CIs). Sensitivity and interaction analyses were also performed.Results: After adjusting for confounders, a higher level of initial hematuria was associated with a 1.43 (95% CI, 1.15–1.78) greater hazard of relapse. Worsening hematuria remarkably increased the risk of short-term relapse (HR, 4.64; 3.29–6.54). Time-averaged hematuria (sHR, 1.35; 1.12–1.63) and cumulative duration of hematuria (sHR, 1.17; 1.02–1.34) were independent predictors of renal progression. Hematuria remission was related to a reduced risk of renal progression over time in patients with positive microhematuria (sHR, 0.63; 0.41–0.96).Conclusions: A higher level of initial hematuria was a remarkable predictor of relapse in patients with PMN, and the magnitude and persistence of microhematuria were independently associated with kidney disease progression.

Validity of urges to smoke measures in predicting smoking relapse during treatment in primary care

In the context of smoking cessation treatment in primary care, identifying patients at the highest risk of relapse is relevant. We explored data from a primary care trial to assess the validity of two simple urges to smoke questions in predicting long-term relapse and their diagnostic value. Of 295 patients who received behavioural support and varenicline, 180 were abstinent at week 9. In this subgroup, we measured time spent with urges to smoke (TSU) and strength of urges to smoke (SUT; both scales 1 to 6 = highest). We used separate regression models with TSU or SUT as predictor and relapse from week 9–26 or week 9–52 as an outcome. We also calculated the sensitivity (SP), specificity and positive predictive values (PPV) of TSU and SUT in correctly identifying patients who relapsed at follow-up. The adjusted odds ratios (aOR) for predicting relapse from week 9–26 were 1.74 per point increase (95% CI = 1.05–2.89) for TSU and 1.59 (95% CI = 1.11–2.28) for SUT. The aORs for predicting relapse from week 9–52 were 2.41 (95% CI = 1.33–4.37) and 1.71 (95% CI = 1.14–2.56), respectively. Applying a cut-point of ≥3 on TSU resulted in SP = 97.1 and PPV = 70.0 in week 9–26, and SP = 98.8 and PPV = 90.0 in week 9–52. Applying a cut-point of ≥4 on SUT resulted in SP = 99.0 and PPV = 85.7 in week 9–26, and SP = 98.8 and PPV = 85.7 in week 9–52. Both TSU and SUT were valid predictors of long-term relapse in patients under smoking cessation treatment in primary care. These simple questions may be useful to implement in primary care.Trial registration: Dutch Trial Register (NTR3067).

Clinical and serological predictors of relapse in pemphigus: a study of 143 patients.

SummaryBackgroundPemphigus is an autoimmune bullous disease mediated by autoantibodies targeting epithelial cell–cell adhesion molecules. Predictors of relapse have not yet been clearly identified.AimsTo identify factors at diagnosis and during follow‐up that could be predictors of relapse.MethodsClinical and immunopathological data at diagnosis, clinical remission and first relapse from patients with pemphigus vulgaris or foliaceus and at least a 36‐month follow‐up were collected retrospectively. Based on the autoantibody profile at diagnosis, three serological patient subsets were devised: (i) anti‐desmoglein (Dsg)1‐positive and anti‐Dsg3‐negative; (iii) anti‐Dsg1‐negative and anti‐Dsg3‐positive; and (iii) anti‐Dsg1‐positive and anti‐Dsg3‐positive.ResultsData from 143 patients were collected. No significant differences were found between relapsers (n = 90) and nonrelapsers (n = 53) for time to remission or for anti‐Dsg1 and anti‐Dsg3 titres at diagnosis and remission. In the analysis of all patients, a higher risk of relapse was found for a body surface area (BSA) score of 3 compared with BSA < 3 (OR = 3.30, 95% CI 1.17–9.28; P = 0.02) and for a positive titre of either anti‐Dsg1 or anti‐Dsg3 autoantibodies at remission compared with both being negative (OR = 2.42, 95% CI 1.21–4.85, P = 0.01). In patients who were anti‐Dsg3‐positive and anti‐Dsg1‐negative at diagnosis, failure to achieve anti‐Dsg3 negativity at clinical remission was a significant predictor of relapse (OR = 7.89, 95% CI 2.06–30.21; P < 0.01). Similarly, failure to achieve anti‐Dsg1 negativity at clinical remission was a significant predictor of relapse in patients with both anti‐Dsg1 and anti‐Dsg3 positivity at diagnosis (OR = 5.74, 95% CI 1.15–28.61; P = 0.03), but not in those who were anti‐Dsg1‐positive/anti‐Dsg3‐negative at diagnosis (OR = 1.08, 95% CI 0.27–4.30; P = 0.91).ConclusionRegardless of pemphigus subtype, autoantibody titre negativity at clinical remission in patients classified based on their anti‐Dsg1 and anti‐Dsg3 profile at diagnosis and BSA were useful tools in predicting relapse.

Donor CD3 Chimerism After Allogeneic Transplantation Predicts Probability Of Relapse For Patients Treated For Acute Myelogenous Leukemia (AML), Acute Lymphoblastic Leukemia (ALL), and Non-Hodkgin's Lymphoma (NHL)

Introduction The ability to predict relapse in patients after HSCT is crucial for tailoring therapy including pre transplant conditioning regimens and post transplant interventions. Donor bone marrow CD34+ cell chimerism analyses has previously been reported to be predictive for post transplant relapse for acute leukemia. Rapid immune reconstitution after HSCT may be important in the development of a robust graft versus leukemia response. Methods We performed for a sequential series of patients a retrospective analysis of donor cell chimerism (DCC) of peripheral blood CD3+ cells at 4 week intervals starting at day 28 after transplantation. Donor bone marrow CD34+ chimerism was evaluated at day 84 after transplantation. Percent chimerism was measured by PCR based amplification of short tandem repeats (STR). From 2009-2012, percent DCC data were collected for patients with ALL (n=39), NHL (n=26), and AML (n=68). Median age at diagnosis was 45 (range 25-69), 51 (range 23-66), and 57 (range 38-75), respectively. Patients received either PBSC or bone marrow cells from related (n=81) or unrelated donors (n=52). At transplantation, patients with ALL were in CR1 (n=27), CR2 (n=4), CR3 (n=1), PIF (n=3), relapse (n=2), PR (n=5); patients with NHL were in PR (n=9), CRU1 (n=4), CRU2 (n=3), Cr1 (n=4), CR2 (n=3), CR3 (n=4); patients with AML were in CR1 (n=38), CR2 (n=6), relapse (n=8), PIF (n=13). Conditioning regimens for patients with ALL were cyclophosphamide (cy) and fractionated total body irradiation (TBI) (n=27) or fludarabine (flu) and melphalan (mel) (n=11). Patients with NHL were conditioned with flu/cy and rituximab (n=15), or flu/mel (n=8). Patients with AML were conditioned with either a myeloablative regimen of flu/busulfan+TBI (n=51), or a reduced intensity regimens of flu/mel or flu/cy/TBI (n=16). Those who had NHL or AML and received unrelated donor cells were given rituximab. Post transplant immunosuppression was tacrolimus and methotrexate for most patients. Patients were censored for relapse or death. For analysis of DCC, patients who relapsed or did not relapse were divided into quartiles by diagnosis. The probability of relapse was tested for quartile groups using chi square analysis. Adjustments were not made for competing risks. Results ALL patients in the upper three quartiles of CD3+ DCCs (1 of 34 patients, median=100%, range=84-100%, [Table 1][1]) compared to patients in the bottom quartile were less likely to relapse (3 of 7 patients, median=94%, range=82-95%, p<0.002). Similarly, the upper 2 quartiles of NHL patients who had at least 95% day 28 CD3+ DCC were less likely to relapse (2 of 16 patients, median 95%, range 63-100%, p<0.007, [Table 1][1]). 7 of 48 patients with AML in the upper 3 quartiles who had day 28 CD3+ DCC of at least 90% (median=100%, range 60-100%) relapsed, trending lower compared to those in the lower quartile (p<0.06). CD3+ DCCs for day 56 and day 84 were not statistically significant for predicting future relapse. View this table: Table 1 CD3+ DCC at 28 days Day 84 CD34+ DCCs were also analyzed as described. The upper quartile of patients with ALL who did not relapse achieved a 100% DCC (1 of 23 patients relapsed, median 100%, range 82-100%, [Table 2][2]). Those that did not achieve 100% DCC for CD34+ cells by day 84 more likely to relapse (p<0.009). For patients with NHL, the upper 3 quartiles of those who did achieve 83% CD34+ DCC (1 of 7, median=90%, range 83-100%, p<0.008) by day 84 were less likely to relapse. The same method was used for patients with AML and those that did achieve 90% CD34+ DCC for cells by day 84 were not likely to relapse (5 of 35, median=96%, range=63-100%, p<0.09). View this table: Table 2 CD34+ DCC at 84 days Conclusions These findings suggest that failure to achieve early donor cell engraftment predicts for relapse. Relapse remains a major cause for treatment failure. Improvements in transplant conditioning may improve early lymphoid (CD3+) and myeloid (CD34+) engraftment and decrease the risk of disease relapse. Early monitoring of CD3+ DCC may identify patients who would benefit from post transplant intervention. Disclosures: No relevant conflicts of interest to declare. [1]: #T1 [2]: #T2

Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer

ObjectiveThe objectives of our study were to assess the association of radiomic and genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC).MethodsIn this retrospective single-centre observational study, we selected 151 surgically treated patients with adenocarcinoma or squamous cell carcinoma who performed baseline [18F] FDG PET/CT. A subgroup of patients with cancer tissue samples at the Institutional Biobank (n = 74/151) was included in the genomic analysis. Features were extracted from both PET and CT images using an in-house tool. The genomic analysis included detection of genetic variants, fusion transcripts, and gene expression. Generalised linear model (GLM) and machine learning (ML) algorithms were used to predict histology and tumour recurrence.ResultsStandardised uptake value (SUV) and kurtosis (among the PET and CT radiomic features, respectively), and the expression of TP63, EPHA10, FBN2, and IL1RAP were associated with the histotype. No correlation was found between radiomic features/genomic data and relapse using GLM. The ML approach identified several radiomic/genomic rules to predict the histotype successfully. The ML approach showed a modest ability of PET radiomic features to predict relapse, while it identified a robust gene expression signature able to predict patient relapse correctly. The best-performing ML radiogenomic rule predicting the outcome resulted in an area under the curve (AUC) of 0.87.ConclusionsRadiogenomic data may provide clinically relevant information in NSCLC patients regarding the histotype, aggressiveness, and progression. Gene expression analysis showed potential new biomarkers and targets valuable for patient management and treatment. The application of ML allows to increase the efficacy of radiogenomic analysis and provides novel insights into cancer biology.