Ronchi, Cristina L

Abstract Objective Advanced adrenocortical carcinoma (ACC) is treated with mitotane alone or combined with cytotoxic chemotherapy, yet outcomes remain poor and prognostic models in this setting are lacking. This study aimed to evaluate the prognostic value of clinical parameters in a large cohort of patients with advanced ACC undergoing systemic therapy. Methods Multicenter, international cohort study investigating 418 patients with advanced ACC (61.5% = women, median age = 52 years) from 11 centers. Patients received mitotane monotherapy (n = 161), etoposide + doxorubicin + cisplatin ± mitotane (n = 178), or second-line regimens (gemcitabine + capecitabine ± mitotane or temozolomide + mitotane, n = 79). Variables included age, cortisol excess, performance status (ECOG-PS), tumor burden, and neutrophil-to-lymphocyte ratio (NLR) at start of therapy. Outcomes were overall survival (OS), time to progression (TTP), and best objective response. Results Tumor burden, cortisol excess, ECOG-PS, and NLR ≥5 independently predicted shorter OS (hazard ratio [HR] 1.55-2.68). We developed an integrated ENSAT Risk Score for Advanced ACC combining these variables: tumor burden (0-2), cortisol excess (0/1), ECOG-PS (0-2), and NLR (0/1). A score >2 (poor-risk) was significantly associated with worse OS and TTP across all treatment groups (HRs for OS: 3.05-3.96; TTP: 2.53-3.08). It also predicted poorer response to mitotane (P < .01) and second-line therapies (P = .04). Conclusions The ENSAT Risk Score for Advanced ACC is a practical, prognostic tool for patients with advanced ACC receiving systemic therapy. Based on accessible clinical and biochemical markers, it can support treatment decisions and facilitate informed discussions in routine care.

Abstract Background Mitotane monotherapy is the standard adjuvant treatment for adrenocortical carcinoma (ACC), yet reliable predictors of treatment response remain lacking. Given the well-recognized interplay between inflammation and cancer progression, serum inflammation-based scores have shown prognostic significance in various malignancies, including ACC in palliative settings. However, their relevance during adjuvant mitotane therapy remains uncertain. This study aimed to assess the prognostic value of inflammation-scores in patients with ACC receiving adjuvant mitotane. Methods Multicenter ENSAT retrospective study including patients with ACC treated with adjuvant mitotane as first-line therapy. Clinical data including age, sex, ENSAT tumor stage, Ki67 index, resection status, and hormone secretion were collected at diagnosis. Inflammation-scores - neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), systemic immune inflammation index (SII), and pan-immune-inflammation value (PIV) - were calculated at diagnosis (pre-surgery) and at mitotane start. Median values of inflammation-scores at diagnosis defined low and high levels. Overall survival (OS) and time to progression (TTP) from mitotane start were the primary endpoints. Results The study included 395 patients (66% female; median age: 51 years). Median time to mitotane start was 54 days (IQR: 32–90). At diagnosis, patients with glucocorticoid excess (n=84) had significantly higher inflammation-scores than those without (n=104): NLR (3.61 vs 2.53), dNLR (2.31 vs 1.72), SII (864.1 vs 679.3), and PIV (531.6 vs 343.1); all p≤0.005. All scores significantly declined after surgery (p<0.05). Higher inflammatory scores at diagnosis were associated with worse OS (NLR: HR=3.85, 95%CI=1.95–7.59, p<0.001; dNLR: HR=3.19, 95%CI=1.67- 6.08, p<0.001; SII: HR=1.97, 95%CI = 1.07–3.61, p=0.03; PIV: HR=2.11, 95%CI=1.13-3.95, p=0.02). However, only the NLR and dNLR remained independently associated with OS at multivariate analysis adjusted for ENSAT stage, Ki67 index, and resection status (p<0.05). At mitotane start (n=372), high SII and PIV were associated with shorter TTP (SII: HR=1.36, 95%CI=1.02-1.82, p=0.03; PIV: HR=1.40, 95%CI=1.04-1-87, p=0.02), with only SII remaining significant at multivariate regression (p=0.04). Conclusions Inflammation-based scores are higher in patients with glucocorticoid excess and decrease postoperatively. NLR and dNLR at diagnosis, and SII at mitotane start, are associated with clinical outcomes in patients with ACC receiving mitotane adjuvant monotherapy. These readily available markers may help improve prognostic stratification in clinical practice.

Abstract Context Urine steroid metabolomics, combining mass spectrometry-based steroid profiling and machine learning, has been described as a novel diagnostic tool for detection of adrenocortical carcinoma (ACC). Objective, Design, Setting This proof-of-concept study evaluated the performance of urine steroid metabolomics as a tool for postoperative recurrence detection after microscopically complete (R0) resection of ACC. Patients and Methods 135 patients from 14 clinical centers provided postoperative urine samples, which were analyzed by gas chromatography–mass spectrometry. We assessed the utility of these urine steroid profiles in detecting ACC recurrence, either when interpreted by expert clinicians or when analyzed by random forest, a machine learning-based classifier. Radiological recurrence detection served as the reference standard. Results Imaging detected recurrent disease in 42 of 135 patients; 32 had provided pre- and post-recurrence urine samples. 39 patients remained disease-free for ≥3 years. The urine “steroid fingerprint” at recurrence resembled that observed before R0 resection in the majority of cases. Review of longitudinally collected urine steroid profiles by 3 blinded experts detected recurrence by the time of radiological diagnosis in 50% to 72% of cases, improving to 69% to 92%, if a preoperative urine steroid result was available. Recurrence detection by steroid profiling preceded detection by imaging by more than 2 months in 22% to 39% of patients. Specificities varied considerably, ranging from 61% to 97%. The computational classifier detected ACC recurrence with superior accuracy (sensitivity = specificity = 81%). Conclusion Urine steroid metabolomics is a promising tool for postoperative recurrence detection in ACC; availability of a preoperative urine considerably improves the ability to detect ACC recurrence.