Predictors Of Relapse Research Articles

Abstract 2497: Modeling the hidden danger of invisible tumor growth in the clinic

Abstract Tumor dormancy, relapse, and resistance are not fully understood. Residual and resistant tumor cells often persist and remain invisible for months or years, despite clean MRI/CT scans following neoadjuvant and/or adjuvant systemic therapies. In current literature reviews we see that residual tumor sizes and tumor detection thresholds can vary widely, further complicating patient prognosis and risk stratification. To address this unmet need, we developed an algorithm to model the timing, frequency, and imaging detection limits of tumor measurements to augment tumor relapse prediction with improved accuracy for clinical application, especially when tumors are below the current detection limits in the clinic. To visualize how long it takes an invisible residual tumor to recur, we generated multiple tumor growth curves to model the remission and relapse time course of 1, 101, 102, 103, and 104 tumor cells, and calculated the time for these therapy-refractory invisible tumors to develop into large 3cm3 MRI/CT-visible tumors. Firstly, we used simple exponential growth curves to model an unimpeded cancer cell doubling time ranging from 2 days to 30 days. Secondly, we used the Spratt model, a modified logistic model, to model the complex tumor growth curves in vivo. Tumor doubling times were varied from 5 to 30 days, indicative of tumor aggressiveness, dynamic tumor/tumor microenvironment interaction, and other tempo-spatial-context-dependency. Treatment frequency and duration were varied as biweekly, monthly, and 6-month office visits to simulate the time course of tumor resistance development following multiple rounds of therapeutic interventions. Additionally, tumor remission and relapse were modeled utilizing smaller residual tumors with longer remission periods. Using these parameters, we generated multiple growth curves to model how invisible and resistant residual tumor sizes, ranging from 10-2 mm3 to 10-6 mm3, will determine the time of diagnosis to time of relapse. Our dynamic tumor progression models demonstrate a rapid tumor relapse time course to reach the detection threshold, highlighting the need for invisible residual tumor modeling for diagnosis and relapse prediction in the clinic. This work highlights the importance of minimizing residual tumor size and reducing drug resistance. We will develop an invisible tumor model as a companion prognostic machine learning tool to identify and quantify therapeutic efficacy, risk stratify patients, and improve outcome and survival in the future. Citation Format: Bryan Hawickhorst, Amy H. Tang. Modeling the hidden danger of invisible tumor growth in the clinic [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2497.

The Paradigm of Desistance and Correctional Interventions: An Interdisciplinary Approach to Relapse Risk Reduction in Sexual Offenders

The criminological approach to relapse is based, on the one hand, on the theories that explain the risk of relapse, including the risk level assessment tools, and on the other hand, on the rehabilitation theories—the Risk-Need-Responsivity (RNR) Model and The Good Live Model (GLM), which explain the mechanisms of reducing the risk of relapse in the assisted desistance paradigm. The objectives of this study focus on identifying the predictors of relapse in correlation with relapse inhibitors that combine a number of personal, psycho-emotional factors with psychopathological, socio-economic, and cultural accents. The method used is that of the case study from the perspective of clinical criminology, referring to forensic psychiatry through specific techniques and working procedures of some institutions in the correctional system—territorial structures of probation (TSP) in cooperation with the penitentiary system. The results of the study focus on the impact of standardized programs on the reduction in the risk of relapse after prison (RRR) and on personal and socio-familial factors involved in post-executional surveillance and post-criminal assistance. In conclusion, the current study highlights the need to corroborate the clinical or subjective assessment of relapse risk with the actual or objective assessment, which also includes the risk of violence in the framework of community monitoring from the perspective of community or social psychiatry.

Abstract 4420: Identification of a novel marker gene predicting recurrence after chemotherapy with DNA-damaging agents by using drug-resistant gastric cancer organoids

Abstract Despite recent advances in gastric cancer therapy, chemotherapy resistance and lack of methods for selecting combination regimens remain major problems. Organoids, which recapitulate the in vivo micro-environment, can be established from surgical specimens with a high success rate, and are widely used for drug sensitivity assays. Cancer organoids are also known to contain abundant amounts of cancer stem cells (CSCs), a subpopulation of tumor cells with self-renewal and differentiation capabilities. CSCs are thought to contribute to tumor initiation, metastasis, and acquiring resistance to chemotherapy by altering their phenotype during the treatment.In this study, we aimed to discover a novel biomarker for predicting multidrug resistance using gastric cancer organoids (GCOs), which provide in vivo-like culture system that more closely resembles tumor cell organization than traditional cell lines, to understand the mechanism of multidrug resistance in cells, including CSCs, under in vivo conditions and to identify novel biomarkers to predict chemoresistance.We evaluated 5-fluorouracil or oxaliplatin-resistant GCOs to find novel biomarkers that reflect multidrug resistance in gastric cancer. To examine the resistance mechanisms, RNA-seq analysis and ex vivo drug sensitivity testing were performed. The association of biomarkers with patient prognosis and chemotherapy efficacy was evaluated using three original cohorts with a total of 230 cases. The results were also validated with two independent public cohorts and a single-cell RNA sequence data. Increased expression of PI3/Elafin was detected in all 5-fluorouracil or oxaliplatin-resistant GCOs. Our findings suggest a potential association of PI3/Elafin expression with ribosome biosynthesis and RNA metabolism under organoid conditions. We also found that PI3/Elafin overexpression promotes 5-fluorouracil/oxaliplatin/cisplatin resistance but not paclitaxel resistance. Immunohistochemical evaluation of Elafin expression revealed that the Elafin-positive gastric cancer group had a poorer outcome, especially in terms of time-to-recurrence. Elafin positivity was also an independent predictor of relapse after chemotherapy with DNA-damaging agents. PI3/Elafin promotes DNA-damaging drug resistance through multiple downstream regulations related to RNA and ribosomal metabolism. We demonstrated that PI3/Elafin contributes to the acquisition of resistance to 5-fluorouracil and platinum drugs in in vivo-like environments and identified GOs related to ribosome and RNA metabolism as novel PI3/Elafin downstream targets. Our results provide new insights into multidrug resistance mechanisms and highlight PI3/Elafin as a novel tool for precise stratification of patients with gastric cancer. Citation Format: Kenji Harada, Naoya Sakamoto, Shingo Sakashita, Motohiro Kojima, Kazuaki Tanabe, Hideki Ohdan, Kohei Shitara, Takahiro Kinoshita, Genichiro Ishii, Wataru Yasui, Atsushi Ochiai, Shumpei Ishikawa. Identification of a novel marker gene predicting recurrence after chemotherapy with DNA-damaging agents by using drug-resistant gastric cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4420.

Abstract 3336: Early detection of tumor relapse, racial disparity, and treatment resistance in triple negative breast cancer

Abstract Introduction: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype that disproportionately affects BRCA1 mutation carriers and young Black/white women. Black/AA patients have the highest mortality and the shortest survival of any racial/ethnic group in the US. Pembrolizumab and neoadjuvant chemotherapy (NACT) has become the standard of care (SOC) for high-risk early-stage TNBC. Pathologic complete response (pCR) predicts good outcome, whereas pathologic incomplete response (pIR) with high residual cancer burden (RCB) is correlated with early tumor relapse, treatment resistance, and poor survival. Many similarly treated patients with identical TNM and RCB classifications experience treatment disparity, distinct relapse rates, and disparate survival. Current methods fall short in predicting early tumor relapse/chemo-resistance/patient survival with high accuracy in the clinic. Methods: We have conducted IHC staining of EGFR, Ki67, SIAH and PD-L1 expression in a large cohort of TNBC patients (> 1,000 patients), of which 48% patients are Black/AA and 48% patients are white patients, from the Sentara Cancer Network and VCU Massey Comprehensive Cancer Center, both of which serve socio-economically-disadvantaged, medically underserved, and underinsured racial/ethnic minorities in low-income communities in Virginia. Results: We found that high SIAH expression in residual tumors reflects ineffective therapy and persistent EGFR/K-RAS/SIAH pathway activation (ON) and predicts early relapse, chemo-resistance, and poor survival. Conversely, low SIAH expression in residual tumors reflects effective therapy and EGFR/K-RAS/SIAH pathway inactivation (OFF) and predicts tumor remission and good survival. We detected a major racial disparity in the large TNBC cohort. Black/AA breast cancer patients suffer a higher MBC mortality and reduced survival compared to their white counterparts in our clinical studies similar to the SEER/CDC databases. Conclusions: We found that persistent EGFR/RAS/SIAH pathway activation is a major driving force in TNBC malignancy. As an evolutionarily conserved RING-domain E3 ligase, SIAH is a new prognostic biomarker for patient risk stratification, tumor relapse prediction, and racial disparity detection in TNBC. We aim to validate the prognostic power of SIAH and develop a SIAH-centered biomarker panel for patient risk stratification and relapse/resistance/survival prediction in TNBC. Citation Format: Amy H. Tang, Richard A. Hoefer, Mary L. Guye, Billur Samli, Janet S. Winston, Jennifer Koblinski, Valentina Robila, Michael O. Idowu, Rick J. Jansen, Harry D. Bear. Early detection of tumor relapse, racial disparity, and treatment resistance in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3336.

Abstract 6478: Relapse prediction of stage III MSS colon cancer by certain cell subtype distribution characteristics in tumor and tumor invasive margin

Colorectal cancer (CRC) is a frequent gastrointestinal malignancy with high rates of morbidity and mortality. Previous studies have shown a significant correlation (p<0.001) between immune score and recurrence time, overall survival, and disease-free survival in subgroups of microsatellite stability (MSS) patients with stage II colon cancer. Current study reviewed 17 stage III MSS CRC patient archived FFPE samples including 11 relapse and 6 no-relapse, to investigate their immune cell features and the correlation to relapse after chemotherapy. IHC control, multiplex immunofluorescence (mIF) panel control and the followed mIF staining were conducted using PN 6-Plex Detection Kit (PhenoVision Bio Co., Itd) targeted CD68, CD3, CD20, panCK, PD-L1 and PD-1. The 17 staining slides were scanned, tumor areas were lined out by pathologist based on H&E staining from the serial section of each sample. Non-tumor region, tumor invasive margin (IM), which was defined as 360μm within and outside of tumor boundary i.e. total 720μm, tumor islands and stromal areas were analyzed using PhenoVision mIF AI analysis system trained from Oncotopix Discovery system (Visiopharm). Statistical analysis exhibited significant correlation of MSS mIF results to relapse rate based on binary logistic regression (p<0.05). Positive cell percentage and positive cell densities were both analyzed in 17 samples. When focused in tumor region, there were significant variated PD-1 negative/CD20 positive cells in tumor stromal region between relapse and non-relapse group (6.64% in non-relapse vs. 2.58%in relapse, p=0.026). Significant differences were observed in PD-L1/CD3 co-positive cell subtype (p=0.01) between relapse and non-relapse groups. Further focus on tumor and IM region, we observed significant more PD-1 negative/CD20 positive cell subtype in IM region compared to tumor area in relapse groups (0.68% tumor vs. 2.21% IM, p=0.0483). Similar trend of less in tumor and more in IM region with CD3 positive and PD-1 negative/CD3 positive cell subtypes was observed in non-relapse group, with p=0.05. Current study indicated that tumor microenvironment carried significant amount variations of cell subtypes between relapse and non-relapse groups. Although there were certain amount of PD-1 negative/CD20 positive cell subtype in relapse group, most located in IM region. The cell distribution feature may be utilized for prognosis prediction of MSS stage III CRCs after chemotherapy to guide patients' health monitoring plans after treatment. Moreover, therapies improve PD-1 negative/CD20 positive and such immune cell subtypes infiltrated into tumor region may improve patient prognosis which need more studies in the field. Citation Format: Hanqing Hu, Hongzhe Sun, Xia Liu, Shuo Han, Lin Zhu, Miao Wang, Zhifu Zhang, Na Li, Guiyu Wang. Relapse prediction of stage III MSS colon cancer by certain cell subtype distribution characteristics in tumor and tumor invasive margin [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6478.

Towards a holistic approach of Giant Cell Arteritis management: Predictors of relapse after initial treatment - results of a prospective follow up study

BackgroundThis study was carried out aiming to: 1. Assess the prognostic role of the clinical as well as ultrasound (US) measures of inflammation for predicting the risk of relapse, and the need for adjunctive biologic therapy. 2. Evaluate the rapidity and sensitivity to change of US measures in the initial months following the diagnosis and initiation of treatment of GCA. 3. Stratify Giant Cell Arteritis (GCA) patients according to their risk of relapse and the possibility of early prediction and classification of the individual subject. This was based on a prospective follow up study which included 67 GCA patients diagnosed according to the EULAR/ACR classification criteria and monitored for 12-months period.ResultsUltrasound OMERACT ultrasonography score for giant cell arteritis (OGUS) scores significantly improved between baseline and 4 weeks (P = 0.001) and the improvement was persistent from 2–12 months (P = 0.01) in non-relapsing patients, whereas negative changes in the OGUS scores, as early as 8-12-weeks of therapy, in comparison to the baseline or last assessment visit, were an early predictor of relapse. Negative changes in the patient’s functional ability and worsening of the disease activity score were also predictors of relapse (p< 0.001).ConclusionThe extent and severity of GCA disease assessed and monitored by health-related quality of life measure, disease activity status as well as ultrasound measures have a prognostic role. US is a useful tool for monitoring GCA disease activity and in association with other conventional biomarkers and disease activity score, they can predict the disease relapse.

Day + 100 bone marrow megakaryocyte count predicts transplant outcome in patients with high-risk myelodysplastic syndrome and acute leukemia.

Megakaryocytes (MKs), the precursor cells of platelets, have essential roles in a variety of pathophysiological processes in the bone marrow (BM) niche. Megakaryocytes maintain hematopoietic stem cell microenvironment through inflammatory and immunological responses. The primary objective of this research was to investigate the clinical impact of BM-MK counts in high-risk myelodysplastic syndrome and acute leukemia patients who underwent allogeneic hematopoietic stem cell transplantation (alloHSCT). Three hundred and forty-six patients (median age, 42 (15-71) years; male/female, 207/139) participated in the study. Based on the BM-MK counts on day + 100 of alloHSCT, the study population was classified into normal/high-MK+100 and low-MK+100 groups. The probabilities of progression-free survival (PFS) and overall survival (OS) were significantly better in the normal/high-MK+100 group (p < 0.001, p < 0.001). Nonrelapse mortality was found to be reduced in the same group of patients (p = 0.012). BM-MK+100 count, which was indicated to be a predictor for relapse after alloHSCT (p = 0.018), represented a considerable impact on PFS and OS (p = 0.017, p = 0.009). Megakaryocytes have regulatory roles in association with a comprehensive cytokine network in the BM microenvironment. Although the localization of MKs may be determinative for their spectrum of efficacy, distinct biological subgroups may also help to clarify the heterogeneity of their functional features. Prospective efforts in larger populations are required to illuminate the potential prognostic role of MKs in alloHSCT recipients.

PSA reduction as predictor of biochemical relapse in low and favourable intermediate prostate cancer treated with radical radiotherapy.

Radiation therapy (RT) is standard treatment for localized prostate cancer (PCa). Prostate-specific antigen (PSA) kinetics, particularly PSA reduction (PSAr) after RT, are emerging as significant prognostic indicators for biochemical control. This retrospective multi-institutional study explores the correlation between PSAr and biochemical relapse-free survival (BRFS). This retrospective multi-institutional study explores the correlation between PSAr and biochemical relapse-free survival (BRFS). 251 low-to-intermediate risk PCa patients treated with RT only were analyzed. Isoeffective RT schedules were: 39 fractions × 2Gy, 28 × 2.55Gy, 16 × 3.5Gy, 5 × 7Gy. Main objective was BRFS, defined as the time from PSA nadir (PSAn) to PSAn plus 2ng/ml. PSAr was defined as the percentage of total PSA reduction from baseline. The optimal PSAr cut-off value was defined as 90%. Patients were stratified by PSAr, baseline PSA, Gleason Score (GS), and RT schedules. GS was 3 + 3 in 120 (48%) patients and 3 + 4 in 131 (52%) patients. After a median follow-up of 36months (30-48), 2 and 5-year BRFS were 97.3% and 95.2%, respectively, in patients with PSAr ≥ 90% and 89.5%, 61.5% in patients with PSAr < 90% (p = 0.00). In the responder population, median time to PSAr 90% was 24months and the median time to PSAn was 28.7months (20-38). At univariate and multivariate analyses, PSAr was the only significant predictor of BRFS [HR 6.519 (95% IC 1.9-22.2), p = 0.003]. PSAr could be a reliable prognostic factor for long-term biochemical control. This study underscores the potential of PSAr as a tool for risk stratification and personalized follow-up strategies in PCa management.

Dynamic Prediction of Rectal Cancer Relapse and Mortality Using a Landmarking-Based Machine Learning Model: A Multicenter Retrospective Study from the Italian Society of Surgical Oncology—Colorectal Cancer Network Collaborative Group

Background: Almost 30% of patients with rectal cancer (RC) who submit to comprehensive treatment experience relapse. Surveillance plays a leading role in early detection. The landmark approach provides a more flexible and dynamic framework for survival prediction. Objective: This large retrospective study aims to develop a machine learning algorithm to profile the patient prognosis, especially the risk and the onset of RC relapse after curative resection. Methods: A cohort of 2450 RC patients were analyzed using landmark analysis. Model A applied a classical cause-specific Cox approach with a landmarking approach, while Model B implemented a landmarking-based RSF (random survival forest) competing risk algorithm. The two models were compared in terms of predictive and interpretative ability. A bootstrapped validation strategy was employed to validate the model’s performance and prevent overfitting. The best-performing hyperparameters were selected systematically, ensuring the model’s robustness within the landmark approach. The study assessed these factors’ importance and interactions using RSF and compared the predictive accuracy to that of the classical Cox model. Results: Model B outperformed Model A (mean C-index 0.95 vs. 0.78), capturing complex interactions and providing dynamic, individualized relapse predictions. Clinical factors influencing survival outcomes were identified across time with the landmark approach allowing for more accurate and timely predictions. Conclusions: The landmark approach offers an improvement over traditional methods in survival analysis. By accommodating time-dependent variables and the evolving nature of patient data, this approach provides a precise tool for profiling RC survival, thereby supporting more informed and dynamic clinical decision-making.

Portal venous circulating tumor cells as a biomarker for relapse prediction in resected pancreatic cancer

BackgroundPancreatic cancer is an aggressive disease with poor prognosis. The only potentially curative treatment option is surgical resection, however recurrence is common. Biomarkers to detect minimal residual disease, assist with risk stratification, relapse and real time monitoring, are required. Circulating tumor cells (CTCs) are a promising liquid biopsy biomarker for solid tumors. However, their role in monitoring minimal residual disease in pancreatic cancer remains to be determined. Our study aimed to investigate whether detection and enumeration of CTCs could predict recurrence and provide monitoring of disease status.MethodParticipants planned for Whipple procedure or partial pancreatectomy were enrolled in this prospective pilot study. Intraoperatively, 7.5 mL of portal and peripheral venous blood were collected, and peripheral venous blood was also collected post-surgery. CTC identification and enumeration were performed using the AccuCyte-CyteFinder platform and CellSieve microfiltration.ResultsOf 29 participants, 20 were confirmed to have epithelial cancer by histopathology, where 15 had pancreatic ductal adenocarcinoma. In those with epithelial cancer, CTCs were detected intraoperatively in 75% of portal venous blood samples, in contrast to 40% detected in peripheral venous blood (median: 6 and 0 per 7.5mL respectively). Only portal venous CTC detection was predictive of pancreatic ductal adenocarcinoma relapse. The positive (> 5) portal venous CTC group had a 6.67 times higher risk of recurring (odds ratio = 20.43, sensitivity = 1.00, specificity = 0.625). Detection of peripheral venous CTCs post-surgery was also correlated with relapse in a small subset of patients.ConclusionsIf validated, CTCs may provide a prognostic and monitoring biomarker in patients with pancreatic cancer undergoing surgery.

Blood-Based Inflammatory Protein Biomarker Panel for the Prediction of Relapse and Severity in Patients with Neuromyelitis Optica Spectrum Disorder: A Prospective Cohort Study (P11-8.015)

Blood-Based Inflammatory Protein Biomarker Panel for the Prediction of Relapse and Severity in Patients with Neuromyelitis Optica Spectrum Disorder: A Prospective Cohort Study (P11-8.015)

A Risk Stratification Tool for Relapse After Intravenous-to-Subcutaneous Switching of Infliximab in Patients with Inflammatory Bowel Diseases

Objectives: A subcutaneous formulation of infliximab was recently approved for maintenance therapy of inflammatory bowel disease (IBD). However, limited clinical experience, particularly with patients on escalated intravenous infliximab regimens, poses challenges for the transition to subcutaneous therapy. We investigated the pharmacokinetics and pharmacodynamics of subcutaneous infliximab to identify early predictors of relapse upon switching. Methods: We repurposed data from a prospective, multicenter trial involving patients with IBD switching from intravenous to subcutaneous infliximab. We estimated each patient’s infliximab clearance using Bayesian forecasting from a pre-switch sample and a population pharmacokinetics model. We performed pharmacodynamics modeling to evaluate pre-switch predictors of post-switch relapse. Relapse was defined as clinical recurrence (partial Mayo score &gt;2 or Harvey–Bradshaw Index &gt;4 leading to therapeutic escalation) or an increase in fecal calprotectin ≥150 μg/g upon switching. Results: Using data from 98 patients with IBD, we identified infliximab clearance and fecal calprotectin as independent predictors of relapse. A two-item risk score stratified patients into low-risk (&lt;19% probability of relapse; 75/98; 77%) and high-risk (≥19% probability of relapse; 23/98; 23%) groups (sensitivity 0.52 [95%CI 0.31−0.73], specificity 0.95 [95%CI 0.87−0.99], positive predictive value 75% [95%CI 48−93%], negative predictive value 87% [95%CI 77−93%]). Our pharmacokinetics–pharmacodynamics model classified patients with and without relapse (p &lt;0.0001) with an area under the receiver operating characteristic curve of 0.83 (95%CI 0.71−0.93). Conclusions: Pre-switch infliximab clearance and fecal calprotectin are accurate predictors of relapse after switching to subcutaneous infliximab. An interactive risk stratification tool facilitates confirmation of a stratified medicine approach to improve infliximab therapy in IBD.

Serum multi-biomarkers for predicting relapse in patients with depressive disorders under psychopharmacotherapy.

Serum multi-biomarkers for predicting relapse in patients with depressive disorders under psychopharmacotherapy.

Psychological and Clinical Parameters as Predictors of Relapse in Alcohol-Dependent Patients During and After Extensive Inpatient Rehabilitation Treatment

Background: Psychological parameters related to alcohol dependence (AD) affect patients’ behavioral and cognitive control, decision making, impulsivity and inhibitory control. People with AD often have a chronic course with a relapse to dependent substance use even after extensive treatment. This study investigated whether the psychological parameters of patients with AD predict (a) premature termination of treatment, and/or (b) relapse into consumption of alcohol from admission until 6 weeks after discharge from an inpatient rehabilitation treatment. Methods: Participants: Alcohol-dependent patients consecutively admitted for a duration of about three months to inpatient rehabilitation treatment in a hospital specialized in substance use disorders. Craving (OCDS-G) and impulsivity (BIS-11; UPPS) were assessed with computerized questionnaires. Attentional bias and inhibitory control were measured with two computer-based experiments (dot-probe task; stop-signal task (SST)). Investigations were conducted at entry (T1); after 6 weeks (T2); and during the last two weeks of the inpatient treatment (T3). Some N = 128 patients finished the first, N = 102 the second and N = 83 the third assessments. Outcome variables were discontinuation of treatment and abstinence or relapse until follow-up 6 weeks after discharge; participants were contacted via telephone. Results: None of the variables are associated with discontinuation of treatment. Poor inhibitory control (SST) and high craving (OCDS-5) levels, measured at T1, are significantly associated with relapse. Higher impulsivity (UPPS) measured at T2 and T3 is significantly associated with relapse. Exploratory analyses showed that older age, longer inpatient treatment duration and time spent in abstinence before rehabilitation treatment were significantly associated with a reduced risk of relapse. Conclusions: Psychological parameters, craving and impulsivity levels did not predict relapse to a high degree. It is assumed that discontinuation of treatment and relapse may be associated with different issues, such as social context, and individual motivation levels. In contrast, the length of both abstinence before admission and of inpatient treatment were significantly associated with abstinence; it is here suggested that recovery time duration may be an underestimated influencing factor regarding relapse in AD patients.

Impact of continuous positive airway pressure therapy withdrawal in patients with obstructive sleep apnea: a randomized controlled trial.

Continuous positive airway pressure (CPAP) is the gold standard for managing moderate-to-severe obstructive sleep apnea (OSA). However, adherence to CPAP usage remains problematic with many patients either intermittently or permanently discontinuing CPAP use. However, the impact of CPAP therapy discontinuation remains unclear. This study aimed to evaluate the effects of complete and intermittent CPAP withdrawal on clinical and objective relapse of OSA. This randomized study involved patients with moderate-to-severe OSA who were compliant with CPAP therapy. All subjects underwent a CPAP efficacy assessment (CPAP check), followed by 1 month of closely monitored CPAP usage. Subjects were then randomized into two groups: (1) complete CPAP withdrawal (NO-CPAP); (2) intermittent CPAP use (INT-CPAP) (using the device every other day). Clinical relapse was assessed daily and defined as reemergence of any of the OSA symptoms. Weekly home sleep testing was performed to assess OSA relapse objectively, defined as an apnea-hypopnea index (AHI) of > 5. A total of 22 patients were included, with 12 subjects assigned to NO-CPAP group and 10 to the INT-CPAP group. Both groups exhibited a rapid recurrence of OSA within 1 week of CPAP discontinuation, with significant increases in AHI, oxygen desaturation index, and time spent with O2 saturation < 90% compared to baseline CPAP-check parameters (p < 0.05). In addition, clinical relapse occurred earlier in ⁓70% of the INT-CPAP group (Median 2.9 days) and 33% in the NO-CPAP group (Median, 3.5 days) (p < 0.05). Age and neck circumference were identified as significant predictors of OSA relapse (p < 0.05). Discontinuation of CPAP therapy, whether completely or intermittently, leads to rapid OSA relapse, with age and neck circumference being key predictors of OSA relapse. These findings underscore the impact of CPAP withdrawal and the need for continuous CPAP adherence to effectively manage OSA. A full trial protocol can be accessed through: https://clinicaltrials.gov/study/NCT05471765 .

NGS-MRD negativity in post-HSCT ALL spares unnecessary therapeutic interventions triggered by borderline qPCR results without an increase in relapse risk.

Monitoring of minimal residual disease (MRD) after hematopoietic stem cell transplantation (HSCT) in patients with acute lymphoblastic leukemia (ALL) is vital for timely therapeutic intervention planning. However, interpreting low-positive results from the current standard method, quantitative PCR (qPCR) of immunoglobulin and T-cell receptor gene rearrangements (IG/TR), poses challenges due to the risk of false positivity caused by non-specific amplification. We aimed to improve MRD detection specificity using the next-generation amplicon sequencing (NGS) of IG/TR rearrangements for better relapse prediction. In pediatric and young adult ALL patients undergoing sequential post-HSCT MRD monitoring, we prospectively re-tested positive non-quantifiable qPCR results with NGS-MRD using the EuroClonality-NGS approach. We were able to confirm 13 out of 47 (27.7%) qPCR positive results using the more specific NGS-MRD method. Out of 10 patients with at least one MRD positivity confirmed by NGS, six relapsed (60%) 1-3.7 months after testing. Among 25 patients with all NGS-MRD results negative, two relapses occurred (8%) after 5.1 and 12.1 months. One-year RFS was 40% versus 96% and 3-year OS was 33.3% versus 94.4% for the NGS-positive and NGS-negative groups, respectively. The difference was not attributable to a varying rate of therapeutic interventions. Six patients out of 14 who had immunosuppressive treatment tapered or received donor lymphocyte infusion in response to MRD positivity developed significant graft versus host disease, leading to one fatality. This underscores the importance of enhancing the post-HSCT relapse risk prediction accuracy through NGS-MRD testing to avoid unnecessary interventions.

Glucocorticoids discontinuation in systemic lupus erythematosus: a single center study

Abstract Objectives To investigate the relapse rate of systemic lupus erythematosus (SLE) patients after glucocorticoids withdrawn, assess the risk factors associated with disease relapse and clarify the outcome of patients with relapse. Methods Data of SLE patients who discontinued glucocorticoids during 2017–2022 were included. Cox regression model was used to estimate the hazard ratio for different factors contributing to lupus relapse. Kaplan-Meier model was used to assess cumulative relapse rate. For those who relapsed, the proportion of patients regaining remission or LLDAS was tracked, and factors associated with remission were analyzed. Results Totally 217 SLE patients were included, of whom 166 experienced disease relapse. The non-relapse rates were 57.3% at 1 year, 19.6% at 3 years, and only 7.8% at 5 years after glucocorticoids withdrawal. Multivariable Cox regression analysis showed self-discontinuation, prior renal or pulmonary impairment or positive anti-dsDNA antibody were independent predictors of SLE relapse. Of the relapsed patients, 21.1% had achieved remission and 54.2% had achieved LLDAS at 12 months of follow-up. Those with high SLEDAI-2K score, anaemia, hypocomplementemia as well as positive anti-dsDNA or anti-Sm antibody had lower remission rates. Conclusions Most SLE patients have difficulty maintaining prolonged stabilization after discontinuing glucocorticoids, and regain remission within a year of relapse. Before discontinuing GC, risk factors associated with recurrence of SLE need to be assessed.

Organ preservation and oncological efficacy of peniscopically controlled CO2 laser excision of penile squamous cell carcinoma: Early and late results in a high-volume center.

Organ preservation and oncological efficacy of peniscopically controlled CO2 laser excision of penile squamous cell carcinoma: Early and late results in a high-volume center.

Prognostic significance of deep sequencing for analysis of measurable residual disease in acute myeloid leukemia with NPM1 mutation

In acute myeloid leukemia with NPM1 mutation, analysis of measurable residual disease (MRD) with reverse transcription quantitative polymerase chain reaction (RT-qPCR) is recommended for response assessment and monitoring after treatment. For rare mutations in NPM1, this is not readily available. Therefore, we evaluated the prognostic value of deep sequencing covering all NPM1 exon 11 variants, using retrospectively analyzed bone marrow samples from 97 patients in remission during treatment. MRD positivity was defined as NPM1 mutation at ≥0.05% variant allele frequency based on a previous comparison with RT-qPCR. Deep sequencing MRD positivity at any time during consolidation predicted relapse-free survival (at 3 years: 23.1 ± 11.7% vs. 70.8 ± 6.1%, p < 0.001) and overall survival (at 3 years: 30.8 ± 12.8% vs. 63.8 ± 6.6%, p = 0.014). In multivariable analysis, MRD status during consolidation was the sole predictor for relapse. In conclusion, deep sequencing of NPM1 has high prognostic value and extends MRD monitoring to patients with rare mutations in NPM1.

Modifiable Factors Influencing Disease Flares in Inflammatory Bowel Disease: A Literature Overview of Lifestyle, Psychological, and Environmental Risk Factors.

Background: A significant concern for patients with Inflammatory Bowel Disease (IBD) is predicting and managing disease flares. While healthcare providers rely on biomarkers, providing conclusive patient advice remains challenging. This review explores the role of lifestyle, psychological health, and environmental exposures in the prediction and management of IBD flares. Methods: This review followed PRISMA guidelines (2020). A structured search was conducted in PubMed for articles published between 2012 and 2024, using free and Medical Subject Heading (MeSH) terms for predicting factors in IBD. Inclusion criteria included studies reporting primary data on modifiable clinical or environmental predictors of IBD relapse, excluding studies on post-operative investigations, treatment cessation, and pediatric or pregnant populations. The Mixed Method Appraisal Tool (MMAT) was used to assess the quality of the studies. Results: Out of 2287 identified citations, 58 articles were included. Several modifiable factors influencing disease flares were identified, including psychological stress, sleep disturbances, smoking, and nutrition. Poor sleep quality and mental health were linked to increased flare risks, while smoking was associated with higher relapse rates in Crohn's disease. Environmental exposures, such as heat waves and high-altitude regions, also contributed. Predictive models integrating clinical, lifestyle, and psychological factors showed promising accuracy but require further refinement. Limitations of this review include the potential for publication bias, variability in flare definitions, and limited sample sizes Conclusions: Key predictors of IBD flares include dietary factors, psychological stress, poor sleep quality, and pharmacological influences. Personalized approaches integrating these predictors can optimize disease control and improve patient outcomes.