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Understanding co-occurrence patterns and prognostic implications of immune-related adverse events is crucial for immunotherapy management. However, previous studies have been limited by sample size and generalisability. In this study, we leveraged a multi-institutional cohort and a population-level database to investigate co-occurrence patterns of and survival outcomes after multi-organ immune-related adverse events among recipients of immune checkpoint inhibitors. In this retrospective study, we identified individuals who received immune checkpoint inhibitors between May 31, 2015, and June 29, 2022, from the Massachusetts General Hospital, Brigham and Women's Hospital, and Dana-Farber Cancer Institute (Boston, MA, USA; MGBD cohort), and between April 30, 2010, and Oct 11, 2021, from the independent US population-based TriNetX network. We identified recipients from all datasets using medication codes and names of seven common immune checkpoint inhibitors, and patients were excluded from our analysis if they had incomplete information (eg, diagnosis and medication records) or if they initiated immune checkpoint inhibitor therapy after Oct 11, 2021. Eligible patients from the MGBD cohort were then propensity score matched with recipients of immune checkpoint inhibitors from the TriNetX database (1:2) based on demographic, cancer, and immune checkpoint inhibitor characteristics to facilitate cohort comparability. We applied immune-related adverse event identification rules to identify patients who did and did not have immune-related adverse events in the matched cohorts. To reduce the likelihood of false positives, patients diagnosed with suspected immune-related adverse events within 3 months after chemotherapy were excluded. We performed pairwise correlation analyses, non-negative matrix factorisation, and hierarchical clustering to identify co-occurrence patterns in the MGBD cohort. We conducted landmark overall survival analyses for patient clusters based on predominant immune-related adverse event factors and calculated accompanying hazard ratios (HRs) and 95% CIs, focusing on the 6-month landmark time for primary analyses. We validated our findings using the TriNetX cohort. We identified 15 246 recipients of immune checkpoint inhibitors from MGBD and 50 503 from TriNetX, of whom 13 086 from MGBD and 26 172 from TriNetX were included in our propensity score-matched cohort. Median follow-up durations were 317 days (IQR 113–712) in patients from MGBD and 249 days (91–616) in patients from TriNetX. After applying immune-related adverse event identification rules, 8704 recipients of immune checkpoint inhibitors were retained from MGBD, of whom 3284 (37·7%) had and 5420 (62·3%) did not have immune-related adverse events, and 18 162 recipients were retained from TriNetX, of whom 5538 (30·5%) had and 12 624 (69·5%) did not have immune-related adverse events. In both cohorts, positive pairwise correlations of immune-related adverse events were commonly observed. Co-occurring immune-related adverse events were decomposed into seven factors across organs, revealing seven distinct patient clusters (endocrine, cutaneous, respiratory, gastrointestinal, hepatic, musculoskeletal, and neurological). In the MGBD cohort, the patient clusters that predominantly had endocrine (HR 0·53 [95% CI 0·40–0·70], p<0·0001) and cutaneous (0·61 [0·46–0·81], p=0·0007) immune-related adverse events had favourable overall survival outcomes at the 6-month landmark timepoint, while the other clusters either had unfavourable (respiratory: 1·60 [1·25–2·03], p=0·0001) or neutral survival outcomes (gastrointestinal: 0·86 [0·67–1·10], p=0·23; musculoskeletal: 0·97 [0·78–1·21], p=0·78; hepatic: 1·20 [0·91–1·59], p=0·19; and neurological: 1·30 [0·97–1·74], p=0·074). Similar results were found in the TriNetX cohort (endocrine: HR 0·75 [95% CI 0·60–0·93], p=0·0078; cutaneous: 0·62 [0·48–0·82], p=0·0007; respiratory: 1·21 [1·00–1·46], p=0·044), except for the neurological cluster having unfavourable (rather than neutral) survival outcomes (1·30 [1·06–1·59], p=0·013). Reliably identifying the immune-related adverse event cluster to which a patient belongs can provide valuable clinical information for prognosticating outcomes of immunotherapy. These insights can be leveraged to counsel patients on the clinical impact of their individual constellation of immune-related adverse events and ultimately develop more personalised surveillance and mitigation strategies. US National Institutes of Health.

The electroencephalogram (EEG) source localization has been one of the most critical brain science research issues. Over the past few decades, the most preeminent ways for solving the EEG inverse problem are to employ prior information or regularization, but this approach is intractable to localize the deep active brain source. Here, the graph Fourier transform (GFT) and the bi-directional long-short term memory (BiLSTM) neural network are introduced to solve the EEG inverse problem in a more efficient and robust way. The presented GFT-BiLSTM in this paper not only fully utilizes spatial information of the brain source signal, but also makes full use of the powerful self-learning ability of the BiLSTM. In the GFT-BiLSTM, the GFT is used for the signal decomposition of the source signal to reduce its dimension. The BiLSTM is adopted to learn the mapping relationship between the brain sources and the recorded EEG. The results show that GFT-BiLSTM outperforms other state-of-the-art inverse models in synthetic data. Regardless of whether the activated region is single or multiple, the area under the curve (AUC) corresponding to GFT-BiLSTM can be reliably above 0.96. When the signal-to-noise ratio (SNR) varies, the GFT-BiLSTM exhibits strong robustness with the highest AUC while the lowest localization error (LE). This fully demonstrates the superiority of GFT-BiLSTM when applied to solve the EEG inverse problem.

BackgroundDupilumab has been added to National Cancer Comprehensive Network guidelines as a therapeutic strategy for managing certain cutaneous immune-related adverse events (cirAEs) from immune checkpoint blockade (ICB). However, little is known about the implications of dupilumab for cancer outcomes in this population. In this multi-institutional study, we evaluate the impact of dupilumab treatment on survival among ICB recipients.MethodsWe conducted a multi-institutional retrospective cohort study of ICB recipients from the Mass General Brigham Healthcare System and Dana-Farber Cancer Institute. The dupilumab group was compared with two control groups who did not receive dupilumab: with and without cirAEs (control groups 1 and 2, respectively) that were 1:2 matched on sex, race, age at ICB initiation, Charlson Comorbidity Score, year of ICB initiation, and ICB type. Manual chart review was performed to obtain cirAE characteristics, systemic glucocorticoid use, dupilumab treatment, vital status, and last contact date. Time-varying multivariable Cox proportional hazards regressions were used to evaluate the impact of dupilumab on overall survival, adjusted for sex, race, age at ICB initiation, ICB type, Charlson Comorbidity Index score, cancer type, cancer stage at ICB initiation, and systemic glucocorticoid use.ResultsA total of 53 cirAE patients treated with dupilumab were compared with two control groups of 106 patients each. Most patients receiving dupilumab demonstrated either complete or partial resolution of their cirAE (88.7%). In multivariable modeling, the overall survival of the dupilumab group was not significantly different from control group 1 (HR=0.74, 95% CI: 0.35 to 1.60, p=0.5) or control group 2 (HR=0.70, 95% CI: 0.32 to 1.51, p=0.4). However, the use of systemic glucocorticoids within 2 years after ICB initiation was associated with poorer overall survival when comparing the dupilumab group to control group 1 (HR=2.03, 95% CI: 1.04 to 3.96, p=0.039) and control group 2 (HR=2.21, 95% CI: 1.25 to 3.91, p=0.006).ConclusionsThis study suggests that dupilumab is an effective therapy for recalcitrant cirAEs and does not adversely impact mortality. Due to the observed detrimental effects of systemic glucocorticoid therapy, this study suggests the need to shift away from systemic glucocorticoid immunosuppression and toward targeted immune modulators for irAE management, though prospective randomized trials are necessary to investigate this.

Prognostic analysis for early-stage (stage I/II) melanomas is of paramount importance for customized surveillance and treatment plans. Since immune checkpoint inhibitors have recently been approved for stage IIB and IIC melanomas, prognostic tools to identify patients at high risk of recurrence have become even more critical. This study aims to assess the effectiveness of machine-learning algorithms in predicting melanoma recurrence using clinical and histopathologic features from Electronic Health Records (EHRs). We collected 1720 early-stage melanomas: 1172 from the Mass General Brigham healthcare system (MGB) and 548 from the Dana-Farber Cancer Institute (DFCI). We extracted 36 clinicopathologic features and used them to predict the recurrence risk with supervised machine-learning algorithms. Models were evaluated internally and externally: (1) five-fold cross-validation of the MGB cohort; (2) the MGB cohort for training and the DFCI cohort for testing independently. In the internal and external validations, respectively, we achieved a recurrence classification performance of AUC: 0.845 and 0.812, and a time-to-event prediction performance of time-dependent AUC: 0.853 and 0.820. Breslow tumor thickness and mitotic rate were identified as the most predictive features. Our results suggest that machine-learning algorithms can extract predictive signals from clinicopathologic features for early-stage melanoma recurrence prediction, which will enable the identification of patients that may benefit from adjuvant immunotherapy.

BackgroundCutaneous immune-related adverse events (cirAEs) are the most common form of immune-related adverse events after immune-checkpoint inhibitor (ICI) treatment, affecting up to 40% of ICI recipients and ranging in severity from mild to life-threatening.1 Although the mechanisms underlying cirAEs remain poorly understood, evidence suggests that cirAEs may be early prognostic indicators of therapeutic response.2 3 Identifying cirAE risk factors can thus help stratify ICI candidates at the highest risk of toxicity and shed light on immune response mechanisms during ICI treatment. The goal of this study is to analyze seasonal and regional variation in cirAE development using a multi-center cohort of ICI recipients.MethodsBriefly, we utilized the TriNetX Dataworks Network which provides deidentified data on more than 90 million patients from 66 health care organizations in the US. We used a validated approach4 based on ICD-10 codes to define the ICI cohort and to identify cirAE cases. We built competing-risks Fine-Gray and Prais-Winsten regression models to test the association between cirAE risk and the season of ICI initiation, while controlling for age, sex, self-reported race and ethnicity, ICI target, ICI year, cancer type, regional variation, and autocorrelation expected in time-series data.ResultsThe ICI cohort comprised 15,253 patients between January 2010 and December 2019, of whom 2,413 patients (15.8%) developed cirAEs. The absolute rate of cirAEs was highest in the fall season (43%), followed by the spring (21%), winter (19%), and summer (17%) seasons (table 1). Using competing-risks and Prais-Winsten models, the risk of cirAE was significantly associated with starting ICI in the winter (β, 0.006; 95% CI, 0.001–0.012, P=0.013) (table 2). This seasonality was robust to sensitivity analysis after excluding all diagnoses of eczema which often flares in the winter.Analysis of geographic variation in cirAE development in the United States revealed the highest rate in the west (35%), followed by the south (29%), northeast (21%), and midwest (16%). Multivariate competing-risks analysis showed significantly increased risk of cirAE development in the west (HR, 2.42; 95% CI, 2.18–2.68; P<0.001), while there was decreased cirAE risk in the northeast (HR, 0.87; 95% CI, 0.77–0.99; P=0.029) (figure 1).ConclusionsSeasonal and geographic variation in cirAE development was observed. The absolute rate of cirAE diagnoses was highest in the fall, while initiating ICI treatment in the winter was associated with significantly increased risk of cirAE development, after multivariate adjustment and correcting for autocorrelation. Within the U.S., ICI recipients in the west had the highest risk of cirAE development.ReferencesThompson LL, Krasnow NA, Chang MS, et al. Patterns of Cutaneous and Noncutaneous Immune-Related Adverse Events Among Patients With Advanced Cancer. JAMA Dermatol. 2021;157(5):577–582. doi:10.1001/jamadermatol.2021.0326Zhang S, Tang K, Wan G, et al. Cutaneous immune-related adverse events are associated with longer overall survival in advanced cancer patients on immune checkpoint inhibitors: A multi-institutional cohort study. J Am Acad Dermatol. 2023;88(5):1024–1032. doi:10.1016/j.jaad.2022.12.048Socinski MA, Jotte RM, Cappuzzo F, et al. Association of Immune-Related Adverse Events With Efficacy of Atezolizumab in Patients With Non-Small Cell Lung Cancer: Pooled Analyses of the Phase 3 IMpower130, IMpower132, and IMpower150 Randomized Clinical Trials. JAMA Oncol. 2023;9(4):527–535. doi:10.1001/jamaoncol.2022.7711Chen W, Wan G, Nguyen N, et al. Identification of cutaneous immune-related adverse events by International Classification of Diseases codes and medication administration. JAAD Int. 2022;9:112–115. doi:10.1016/j.jdin.2022.08.001Abstract 1251 Table 1Basic characteristic of the study populationAbstract 1251 Table 2Prais-Winsten regression of 6-month cirAE risk on ICI start season. Spring was used as a reference groupAbstract 1251 Figure 1Seasonal and regional variation in cirAEs. (A) Forest plot of the multivariate competing-risks regression model (Fine-Gray) for cirAE development, showing the hazard ratio of cirAE compared to no-irAE controls. Geographic variation is noted. (B and C) Bar graphs showing the frequency of ICI initiation and cirAE diagnosis per month and season, respectively. (D and E) Line graphs showing the predicted 1-year risk of cirAE per month and season, respectively. Predictions were made using the Fine-Gray model from (A)

Melanoma in advanced stages is one of the most aggressive tumors and the deadliest of skin cancers. To date, the histopathological staging focuses on tumor thickness, and clinical staging is a major estimate of the clinical behavior of primary melanoma. Here we report on an observational study with in-depth molecular profiling at the protein level including post-translational modifications (PTMs) on eleven primary tumors from melanoma patients. Global proteomics, phosphoproteomics, and acetylomics were performed on each sample. We observed an up-regulation of key mitochondrial functions, including the mitochondrial translation machinery and the down-regulation of structural proteins involved in cell adhesion, the cytoskeleton organization, and epidermis development, which dictates the progression of the disease. Additionally, the PTM level pathways related to RNA processing and transport, as well as chromatin organization, were dysregulated in relation to the progression of melanoma. Most of the pathways dysregulated in this cohort were enriched in genes differentially expressed at the transcript level when similar groups are compared or metastasis to primary melanomas. At the genome level, we found significant differences in the mutation profiles between metastatic and primary melanomas. Our findings also highlighted sex-related differences in the molecular profiles. Remarkably, primary melanomas in women showed higher levels of antigen processing and presentation, and activation of the immune system response. Our results provide novel insights, relevant for developing personalized precision treatments for melanoma patients.

BackgroundHigh-dose systemic immunosuppression (ISP) is associated with poorer survival outcomes in cancer patients treated with immune checkpoint inhibitors (ICIs).1–3 However, the effect of ISP timing on survival is not well-studied. The aim of this retrospective study is to examine the association between immunosuppression timing and overall survival among ICI recipients using a large multi-institutional cohort.MethodsWe identified 2,077 ICI recipients who did not receive chemotherapy within 18 months before or after ICI initiation at the Mass General Brigham Healthcare System and the Dana-Farber Cancer Institute from 2011–2021 (figure 1). ISP use was defined as either 1) at least 10 mg/day prednisone equivalent of glucocorticoids for at least a week, 2) 1 dose of biologic immunosuppression, or 3) at least 1 week of non-steroidal systemic immunosuppression within the time window. Using this definition, 912 patients received ISP within 18 months before or after ICI initiation. Case and control cohorts are defined in (table 1). Multivariate Cox proportional hazard models were computed at different times relative to ICI initiation, adjusting for demographics, Charlson comorbidity index at ICI initiation, ICI type, and cancer type. The control group for all analyses was patients who did not receive ISPs (n=1,165).ResultsThe median follow-up was 23.0 (IQR: 6–42) months from ICI start. High-dose systemic glucocorticoids were the most common form of ISP (97.7%), followed by biologics (11.7%), and non-steroidal systemic immunosuppressants (10.9%). After covariate adjustment, we found that ISP use within 18 months before or after ICI initiation was associated with significantly increased mortality (HR: 1.44; 95% CI: 1.27–1.64; p<0.001)(table 2). When performing sliding window time analyses, we found that the increased risk of mortality escalated with ISP administration closer to ICI initiation and was the highest when patients received ISP within 1 month before or after ICI initiation (HR: 2.49; 95% CI: 2.05–3.01; p<0.001)(figure 2). The negative effect of ISP exposure tapered off 8–12 months after ICI initiation (HR: 1.29; 95% CI: 0.89, 1.29; q-value: 0.56)(figure 3).ConclusionsOverall, high-dose systemic immunosuppression (primarily glucocorticoid immunosuppression as observed in this cohort) is associated with increased mortality among ICI recipients and correlates with increasingly poorer survival the closer it is administered to ICI initiation. However, the deleterious effects of ISP seem to taper off if administered more than 8 months after ICI initiation. Clinicians should include the timing of ISP administration in the risk and benefit analysis of ISP therapy when counseling cancer patients receiving ICI.ReferencesBai X, Hu J, Betof Warner A, et al. Early Use of High-Dose Glucocorticoid for the Management of irAE Is Associated with Poorer Survival in Patients with Advanced Melanoma Treated with Anti-PD-1 Monotherapy. Clinical Cancer Research. 2021;27(21):5993–6000. doi:10.1158/1078–0432.CCR-21–12833.Petrelli F, Signorelli D, Ghidini M, et al. Association of Steroids Use with Survival in Patients Treated with Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis. Cancers (Basel). 2020;12(3):546. doi:10.3390/cancers120305462.Tison A, Quéré G, Misery L, et al. Safety and Efficacy of Immune Checkpoint Inhibitors in Patients With Cancer and Preexisting Autoimmune Disease: A Nationwide, Multicenter Cohort Study. Arthritis Rheumatol. 2019;71(12):2100–2111. doi:10.1002/art.41068Ethics ApprovalThis study has been approved by the Mass General Brigham Institutional Review Board (protocol number 2020P002307).Abstract 1273 Figure 1Patient inclusion and exclusion criteriaAbstract 1273 Table 1Clinicopathologic baseline characteristic of ICI patientAbstract 1273 Table 2Association of ISP use with overall survival using a multivariate Cox proportional hazards model for all patientsAbstract 1273 Figure 2Survival of ICI recipients based on timing of ISP relative to ICI initiation. Table shows the hazard ratio of the case cohort within each window relative to the overall control cohort using a multivariate Cox proportional hazards model, adjusting for demographics, Charlson Comorbidity Index at ICI initiation, ICI type, and cancer type.Abstract 1273 Figure 3Risk of mortality among ICI recipients starting ISP within a 4-month sliding window. This figure shows the number of cases in each time window. The same overall control cohort of 1,165 patients ws used for all sliding windows. Sliding windows are in 4-month increments. Months starting with n refer to months prior to ICI initiation and thos starting with p refer to months post-ICI initiation.

BackgroundImmune-related adverse events (irAEs) induced by immune checkpoint inhibitor (ICI) therapy can involve multiple organ systems, of which cutaneous irAEs (c-irAEs) are the most common.1–5 Understanding co-occurrence patterns and prognostic outcomes of irAEs is critical for immunotherapy management. However, previous studies have been limited by cohort size, thus limiting generalizability.6–8 In addition, the prior study approaches primarily utilized pairwise comparison analyses, which limited the examination of irAE relationships to two organ systems at a time. In this study, we leverage a population-level database and compare results to a multi-institutional cohort from a tertiary-level academic healthcare system to investigate the co-occurrence patterns irAEs and their impact on immunotherapy outcomes through non-negative matrix factorization (NMF),9 which allows for multi-organ analyses.MethodsAfter propensity-matching in a 1:2 ratio based on demographic and cancer-related variables and exclusion of ambiguous cases, the study analyses included 9,273 patients in the Mass General Brigham Healthcare System (MGB) cohort and 23,689 patients in the TriNetX network (figure 1). The identification of irAEs was based on ICD codes. Pairwise correlation analysis and NMF were conducted to investigate the co-occurrence patterns. Multivariate landmark analyses were conducted to evaluate the associated impact on overall survival, adjusting for demographics, cancer type, and ICI type.ResultsCharacteristics of the TriNetX and MGB are shown in (table 1). Pairwise co-occurrence analyses showed patients with c-irAEs were at increased risk of developing an irAE in nine of the eleven organ systems evaluated. The co-occurrence of c-irAEs and non-cutaneous irAEs (nc-irAEs) was associated with improved survival (HR:0.68, CI, 0.61–0.76; p<0.001) (table 2). NMF identified four unique patient clusters, of which three were consistent between the TriNetX and MGB cohorts: c-irAEs, endocrine irAEs, and multiple internal organ irAEs (comprising mostly neurologic, respiratory, gastrointestinal irAEs) (figure 2). The Cutaneous and endocrine clusters showed strongly favorable prognoses across all landmark times (table 3). The endocrine-dominant cluster displayed a better prognosis (MGB: HR=0.48, p<0.001; TriNetX: HR=0.58, p<0.001) compared to the Cutaneous-dominant cluster (MGB: HR=0.55, p<0.001; TriNetX: HR=0.65, p<0.001).ConclusionsOur study demonstrates that patients who develop c-irAEs are at significantly increased risk of developing toxicities in other organs. This emphasizes the importance of monitoring, diagnosing, and managing c-irAEs given their valuable prognostic benefit. In addition, we specifically found a significant survival benefit among patients who develop cutaneous and endocrine irAEs. This may suggest underlying mechanisms that differ from other ICI and organ system interactions, which will require future studies to elucidate.ReferencesRamos-Casals M, Brahmer JR, Callahan MK, et al. Immune-related adverse events of checkpoint inhibitors. Nat Rev Dis Primers. 2020;6(1):1–21. Doi:10.1038/s41572–020-0160–6Puzanov I, Diab A, Abdallah K, et al. Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC) Toxicity Management Working Group. J Immunother Cancer. 2017;5(1):95. Doi:10.1186/S40425–017-0300-ZBrahmer JR, Lacchetti C, Schneider BJ, et al. Management of immune-related adverse events in patients treated with immune checkpoint inhibitor therapy: American society of clinical oncology clinical practice guideline. Journal of Clinical Oncology. 2018;36(17):1714–1768. Doi:10.1200/JCO.2017.77.6385Le TK, Brown I, Goldberg R, et al. Cutaneous Toxicities Associated with Immune Checkpoint Inhibitors: An Observational, Pharmacovigilance Study. J Invest Dermatol. 2022;142(11):2896–2908.e4. doi:10.1016/J.JID.2022.04.020Wongvibulsin S, Pahalyants V, Kalinich M, et al. Epidemiology and risk factors for the development of cutaneous toxicities in patients treated with immune-checkpoint inhibitors: A United States population-level analysis. J Am Acad Dermatol. 2022;86(3):563–572. Doi:10.1016/J.JAAD.2021.03.094Chieng JHL, Htet ZW, Zhao JJ, et al. Clinical Presentation of Immune-Related Endocrine Adverse Events during Immune Checkpoint Inhibitor Treatment. Cancers (Basel). 2022;14(11):2687. Doi:10.3390/CANCERS14112687Yamada K, Nakamura M, Yamamura T, et al. Clinical characteristics of gastrointestinal immune-related adverse events of immune checkpoint inhibitors and their association with survival. World J Gastroenterol. 2021;27(41):7190. Doi:10.3748/WJG.V27.I41.7190Asdourian MS, Shah N, Jacoby T V, et al. Development of multiple cutaneous immune-related adverse events among cancer patients after immune checkpoint blockade. J Am Acad Dermatol. 2023;88(2):485–487. Doi:10.1016/j.jaad.2022.06.030Pedregosa FABIANPEDREGOSA F, Michel V, Grisel OLIVIERGRISEL O, et al. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research. 2011;12(85):2825–2830. Accessed February 24, 2023. http://jmlr.org/papers/v12/pedregosa11a.htmlEthics ApprovalReviewed and approved by Mass General Brigham IRB (Protocol #2020P002179)Abstract 1241 Table 1Characteristics of the MGB and TriNetX cohortsAbstract 1241 Table 2Survival outcomes of multi-organ toxicity among patients with c-irAEsAbstract 1241 Table 3Survival outcomes of patients cluster identified by NMFAbstract 1241 Figure 1The study populationAbstract 1241 Figure 2The results of NMF and hierarchical clustering on the consensus matrix. (A, B) The NMF results and clusters on the TriNetX cohort; C-D: The NMF results and clusters on the MGB cohort. The NMF decomposed the irAE count matrix into two low-rank matrices, representing the organ-level irAE factors (referred to as ‘basis’; A, C) and the weights of irAE factors that comprise each patient (referred to as ‘weight’; B and D), respectively. For the basis matrix, rows are organ systems, and columns are the irAE factors, each named by the dominant organ systems. For the weight matrix, columns are patients, rows are irAE factors, and the clustering results are presented at the top. Similar patterns were observed between the two basis matrices (A, C). Patients in both cohorts could be categorized into four groups (B, D) Cutaneous, Cutaneous + Internal

BackgroundMelanoma mortality has steadily decreased since the introduction of immune checkpoint inhibitors (ICIs) to manage advanced-stage disease (stage III/IV).1 Although ICIs have prolonged survival, this therapeutic class is associated with toxicities, of which cutaneous immune-related adverse events (cirAEs) are the most common2 and may serve as early biomarkers of therapeutic efficacy.3 4 The recent approval of adjuvant ICI therapy for patients with stage IIB/IIC melanoma raises concerns about the appropriateness and timing of immunotherapy in this population,5 especially when most patients will not experience disease recurrence following surgical resection alone.6 In this study, we compare cirAE development and overall survival in patients with early-stage (stage I/II) primary cutaneous melanoma that recurred at an advanced stage (recurred) as compared to those with advanced-stage melanoma at time of diagnosis (advanced).MethodsWe identified 134 ICI recipients with recurrent melanoma and 134 matched ICI recipients with advanced melanoma from the Mass General Brigham and Dana-Farber Cancer Institute. Manual chart reviews were conducted to ascertain the presence of cirAEs.3 Pearson’s chi-squared test for categorical variables and t-test for continuous variables were used for comparisons. Cox proportional hazards (CoxPH) modeling was performed, adjusted for demographics, Charlson comorbidity score (CCS), ICI type, melanoma stage at ICI initiation, histologic type, primary melanoma anatomic site, presence of ulceration, and presence of tumor-infiltrating lymphocytes within the primary melanoma.ResultsTable 1 presents the characteristics of the study population. CoxPH models demonstrated no differences in cirAE development (HR:0.68; 95% CI:0.39–1.20; p=0.2) and overall survival (HR:1.21; 95% CI:0.69–2.12; p=0.5) (table 2).ConclusionsOur study shows that patients with recurrent early-stage primary melanoma are as likely to develop cirAEs (an early biomarker of therapeutic efficacy in this population) and experience similar overall survival as patients with advanced-stage melanoma at the time of diagnosis. Given that most stage IIB and IIC melanomas do not recur after excision and the high risk of ICI toxicities, adoption of adjuvant immunotherapy in this population has been slow, particularly in the absence of accurate biomarkers for identification of high-risk patients. Our findings are, however, reassuring that ICI response is similar among early-stage patients who experience recurrence and the advanced-stage melanoma population in which ICI therapy has been used more extensively. Given these observations, it is important to inform patients of the potential benefits and risks of delaying ICI therapy in the setting of early-stage disease and the expected response to ICI therapy in the event of melanoma recurrence.ReferencesNaik PP. Current Trends of Immunotherapy in the Treatment of Cutaneous Melanoma: A Review. Dermatol Ther (Heidelb). 2021;11(5):1481–1496. doi:10.1007/s13555-021-00583-zTattersall IW, Leventhal JS. Focus: Skin: Cutaneous Toxicities of Immune Checkpoint Inhibitors: The Role of the Dermatologist. The Yale Journal of Biology and Medicine. 2020;93(1):123.Zhang S, Tang K, Wan G, et al. Cutaneous immune-related adverse events are associated with longer overall survival in advanced cancer patients on immune checkpoint inhibitors: a multi-institutional cohort study. Journal of the American Academy of Dermatology. Jan 31, 2023; doi:10.1016/j.jaad.2022.12.048Nguyen N, Wan G, Ugwu-Dike P, et al. Influence of melanoma type on incidence and downstream implications of cutaneous immune-related adverse events in the setting of immune checkpoint inhibitor therapy. J Am Acad Dermatol. 2023;88(6):1308–1316. doi:10.1016/j.jaad.2023.02.014FDA Center for Drug Evaluation and Research. FDA approves pembrolizumab for adjuvant treatment of Stage IIB or IIC melanoma. FDA.gov. Published December 6, 2021. Accessed December 11, 2022. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-pembrolizumab-adjuvant-treatment-stage-iib-or-iic-melanomaBleicher J, Swords DS, Mali ME, et al. Recurrence patterns in patients with Stage II melanoma: The evolving role of routine imaging for surveillance. Journal of Surgical Oncology. 2020;122(8):1770–1777. doi:10.1002/jso.26214Ethics ApprovalReviewed and exempted by Mass General Brigham IRB (Protocol #2020P002179).Abstract 554 Table 1Characteristics of the study populationAbstract 554 Table 2CoxPH models for overall survival and cirAE development between patients with recurred melanoma and patients with advanced melanoma at diagnosis.

Many robust variants of Principal Component Analysis remove outliers from the data and compute the principal components of the remaining data. The robust centered variant requires knowledge of the center of the non-outliers. Unfortunately, the center of non-outliers is unknown until after the outliers are determined, and using an inaccurate center may lead to the detection of wrong outliers. We demonstrate this problem in several known robust PCA algorithms. We describe a method that implicitly centers the non-outliers, implemented by appending a constant value (bias) to each data point. This bias method can be used with “black box” robust PCA algorithms by augmenting their input with minimal change to the algorithm itself.