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PURPOSE There is strong evidence that leisure-time physical activity is protective against postmenopausal breast cancer risk but the association with premenopausal breast cancer is less clear. The purpose of this study was to examine the association of physical activity with the risk of developing premenopausal breast cancer. METHODS We pooled individual-level data on self-reported leisure-time physical activity across 19 cohort studies comprising 547,601 premenopausal women, with 10,231 incident cases of breast cancer. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% CIs for associations of leisure-time physical activity with breast cancer incidence. HRs for high versus low levels of activity were based on a comparison of risk at the 90th versus 10th percentiles of activity. We assessed the linearity of the relationship and examined subtype-specific associations and effect modification across strata of breast cancer risk factors, including adiposity. RESULTS Over a median 11.5 years of follow-up (IQR, 8.0-16.1 years), high versus low levels of leisure-time physical activity were associated with a 6% (HR, 0.94 [95% CI, 0.89 to 0.99]) and a 10% (HR, 0.90 [95% CI, 0.85 to 0.95]) reduction in breast cancer risk, before and after adjustment for BMI, respectively. Tests of nonlinearity suggested an approximately linear relationship ( Pnonlinearity = .94). The inverse association was particularly strong for human epidermal growth factor receptor 2–enriched breast cancer (HR, 0.57 [95% CI, 0.39 to 0.84]; Phet = .07). Associations did not vary significantly across strata of breast cancer risk factors, including subgroups of adiposity. CONCLUSION This large, pooled analysis of cohort studies adds to evidence that engagement in higher levels of leisure-time physical activity may lead to reduced premenopausal breast cancer risk.

Significance Statement Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice. Background Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon. Methods We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators. Results A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8–35.5) between 2005 and 2012 and 57.5 (IQR, 53.3–59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96–629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0–6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies. Conclusions Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

Introduction: The real-world outcomes in patients (pts) with PCALCL in the era of targeted therapies like Brentuximab Vedotin (BV) is not well defined due to lack of large multicenter studies. We conducted a multicenter retrospective RWA to assess patient and disease characteristics, treatment patterns, survival outcomes and impact of novel therapies in this rare type of cutaneous T cell lymphoma (CTCL). Methods: A total of 95 adult (≥18 years) pts from 8 academic institutions in the United States diagnosed from 2010-2022 were included in the analysis. The study was approved by the Institutional Review Boards at the respective sites. Demographic and disease factors were summarized by descriptive statistics. Overall survival (OS) was estimated by Kaplan-Meier method and compared using log rank method. Results: In our cohort, the median age at diagnosis was 63 (range 18-93) years. The majority of pts were male 60%, white 79%, and had good performance status (PS) ECOG 0-1 (93%). Median time from initial presentation to diagnosis was 1.8 (range 0-211) months. Most common initial skin presentation was tumor 46% (44/95), followed by plaques 27% (26/95) and patches 15% (14/95). No pt presented with erythroderma. Median size of the largest lesion was 2 (range 0.5-20) cm. 63% had early stage (IA-IIA) disease and 86% had &lt;5 skin lesions at the time of initial diagnosis. Furthermore, palpable lymph node (LN) (10%) and elevated LDH (18%) were uncommon at diagnosis. Initial treatments include localized radiation 60%, surgical excision 21% and topical steroids 11%. A small subset of pts received systemic treatments like CHOP 13% (12/95), BV 8% (8/95) and oral methotrexate 7% (7/95) as frontline therapy. A proportion of pts received XRT with CHOP (6/12) and BV (2/8). The overall response rate (ORR) to initial therapy was 68% (65/95) with 61% achieving a CR and 17% had primary refractory disease (stable and progressive disease). Relapse rate after 1st line therapy was 52% (49/95). In our cohort a total of 22 pts received BV after frontline therapy, of which 19 were BV naïve and 3 were re-treated. At the time of last follow up, 27% of our cohort were still on treatment, 78% were alive and 21% were dead; only 3% of deaths were attributed to the lymphoma. The median OS was 128 months (95% CI: 78.4-NA) (Figure 1) with a median follow up of 42 (range 0.5-123.5) months. The 5-year OS was 77%. On univariate analysis, older age (≥65 vs &lt;65 years) (median OS 78 vs 128 months; p=0.004) and higher number of lesions (5-10 vs &lt;5) (mOS 34 vs 128 months; p=&lt;0.0001) were significant associated with OS (Table 1). Type and size of the skin lesions, presence of palpable LN, elevated LDH, stage, and treatment modalities had no impact on OS. Results of multivariate analysis will be presented at the conference. Conclusion: In this large multicenter RWA of PCALCL, excellent long-term survival was observed following frontline therapies that were mostly skin directed. The use of systemic therapies including BV were infrequent even in relapsed disease. Older age and increased number of skin lesions were associated with poor OS.

Introduction: Lineage switch (LS) refers to the transformation of acute leukemia from one cell lineage to another (e.g., lymphoid (ALL) to myeloid (AML)). This rare phenomenon, distinct from treatment induced malignancy (i.e., t-AML) and mixed phenotype acute leukemia (MPAL), is increasingly being observed following cell surface antigen targeting. Given challenges in the diagnosis and treatment of LS, Project EVOLVE was developed to globally identify cases of LS following immunotherapy. Methods: A protocol and data collection form for this IRB exempt study was widely disseminated to capture deidentified LS case information across multiple centers and cancer consortia. This included collection of data from published reports of LS, with authors contacted to obtain additional information. For this analysis, LS was defined by the emergence of cell-surface markers warranting reclassification of the original leukemia as a different lineage derivation based on the immunophenotype, including cases of AML emerging alongside the original ALL. “Confirmed” LS cases included those where retention of original cytogenetic or molecular aberrations and/or the clonal immunoglobulin rearrangement patterns were verified to confirm the clonal relationship. “Suspected” LS cases included those where samples to confirm clonality marker retention could not be obtained, but the clinical presentation was consistent with LS. The term “transition” was applied when immunophenotypic shifts were transient. Cases with new cytogenetic abnormalities unrelated to the original diagnosis and compatible with t-AML were excluded. Statistical analysis was primarily descriptive. Data cut-off was July 26, 2023. Results: A total of 58 cases were identified, including 19 cases referenced in prior publications. Of the 58, 11 cases were excluded from this initial analysis, including: 4 cases of t-AML, 2 cases of T-ALL to AML, and 5 “transition” cases. Collectively, 47 cases of LS (43 “confirmed”; 4 “suspected”), spanning across 3 continents and 8 countries, were analyzed. (Fig. 1A) Cases included transition from B-ALL to AML in 36 (76.6%) and to MPAL/biphenotypic/ambiguous lineage in 11 (23.4%). Two likely had MPAL at diagnosis and a third with chronic myeloid leukemia. The median age at initial diagnosis was 8.4 years (range, 1 day-76.5 years); median age at LS presentation was 11.0 years (range 0.4-77.3 years). Twenty-three (48.9%) were male and 19 (40.4%) had prior stem cell transplant (SCT). Baseline cytogenetics showed KMT2A rearrangement in 27 (57.4%). Baseline myeloid antigen co-expression was seen in 22 of 23 patients with submitted data, but variation in degree of expression across patients and antigens was substantial. The most proximal immunotherapy prior to development of LS was CAR T-cells in 23 (48.9%) and blinatumomab in 24 (51.1%). The median time from the most proximal immunotherapy to development of LS was 1.6 months (range, 7 days-36.5 months). In 7 (29.2%) patients receiving blinatumomab, LS developed during the infusion. LS presented as isolated marrow relapse in 27 (57.4%), isolated CNS in 2 (4.3%), isolated non-CNS extramedullary disease in 3 (6.4%), combined relapse in 14 (29.8%) and unreported in 1. First line treatment for LS was chemotherapy induction in 31 (66.0%), palliative care/no therapy in 8 (17.0%), and alternative therapies in the remaining 8 (17.0%). In 35 (74.5%) patients, remission induction was the goal of first line therapy. Fifteen (31.9%) achieved a complete remission (CR) of whom 2 were treated with palliative intent. Across all patients, 8 (17.0%) are alive in remission, the longest being 4.7 years from LS diagnosis; 2 (4.3%) are alive with active LS and 37 (78.7%) died from LS, their original disease, or complications of treatment of LS (Fig 1B). For those alive in CR (n=8), 7 (87.5%) proceeded to a consolidative SCT for treatment of LS and 1 patient, an octogenarian remains in remission after AML directed therapy. Conclusions: LS is emerging as an important mechanism of immune escape following immunotherapy. Project EVOLVE provides the largest dataset of patients with LS to date. This systematic, international effort reveals substantial complexity and variability in diagnosing and managing LS. Unfortunately, outcomes following LS are grim, underscoring the critical need to identify risk factors of and optimal therapies for this leukemia transformation.