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Background The HYPO-RT-PC trial compared conventionally fractionated radiotherapy with ultra-hypofractionated radiotherapy in patients with localised prostate cancer. Ultra-hypofractionation was non-inferior to conventional fractionation regarding 5-year failure-free survival and toxicity. We aimed to assess whether patient-reported quality of life (QOL) differs between conventional fractionation and ultra-hypofractionation up to 6 years after treatment in the HYPO-RT-PC trial. Methods HYPO-RT-PC is a multicentre, open-label, randomised, controlled, non-inferiority, phase 3 trial done in 12 centres (seven university hospitals and five county hospitals) in Sweden and Denmark. Inclusion criteria were histologically verified intermediate-to-high-risk prostate cancer (defined as T1c-T3a with one or two of the following risk factors: stage T3a; Gleason score >= 7; and prostate-specific antigen 10-20 ng/mL with no evidence of lymph node involvement or distant metastases), age up to 75 years, and WHO performance status 0-2. Participants were randomly assigned (1:1) to conventional fractionation (78.0 Gy in 39 fractions, 5 days per week for 8 weeks) or ultra-hypofractionation (42.7 Gy in seven fractions, 3 days per week for 2.5 weeks) via a minimisation algorithm with stratification by trial centre, T-stage, Gleason score, and prostate-specific antigen. QOL was measured using the validated Prostate Cancer Symptom Scale (PCSS) and European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire (EORTC QLQ-C30) at baseline, the end of radiotherapy, months 3, 6, 12, and 24 after radiotherapy, every other year thereafter up to 10 years, and at 15 years. The primary endpoint (failure-free survival) has been reported elsewhere. Here we report QOL, a secondary endpoint analysed in the perprotocol population, up to 6 years after radiotherapy. The HYPO-RT-PC trial is registered with the ISRCTN registry, ISRCTN45905321. Findings Between July 1, 2005, and Nov 4, 2015, 1200 patients were enrolled and 1180 were randomly assigned (conventional fractionation n=591, ultra-hypofractionation n=589); 1165 patients (conventional fractionation n=582, ultra-hypofractionation n=583) were included in this QOL analysis. 158 (71%) of 223 patients in the conventional fractionation group and 146 (66%) of 220 in the ultra-hypofractionation group completed questionnaires at 6 years. The median follow-up was 48 months (IQR 25-72). In seven of ten bowel symptoms or problems the proportion of patients with clinically relevant deteriorations at the end of radiotherapy was significantly higher in the ultra-hypofractionation group than in the conventional fractionation group (stool frequency [p<0.0001], rush to toilet [p=0.0013], flatulence [p=0.0013], bowel cramp [p<0.0001], mucus [p=0.0014], blood in stool [p<0.0001], and limitation in daily activity [p=0.0014]). There were no statistically significant differences in the proportions of patients with clinically relevant acute urinary symptoms or problems (total 14 items) and sexual functioning between the two treatment groups at end of radiotherapy. Thereafter, there were no clinically relevant differences in urinary, bowel, or sexual functioning between the groups. At the 6-year followup there was no difference in the incidence of clinically relevant deterioration between the groups for overall urinary bother (43 [33%] of 132 for conventional fractionation vs 33 [28%] of 120 for ultra-hypofractionation; mean difference 5.1% [95% CI -4.4 to 14.6]; p=0.38), overall bowel bother (43 [33%] of 129 vs 34 [28%] of 123; 5.7% [-3.8 to 15.2]; p=0.33), overall sexual bother (75 [60%] of 126 vs 59 [50%] of 117; 9.1% [-1.4 to 19.6]; p=0.15), or global health/QOL (56 [42%] of 134 vs 46 [37%] of 125; 5.0% [-5.0 to 15.0]; p=0.41). Interpretation Although acute toxicity was higher for ultra-hypofractionation than conventional fractionation, this long-term patient-reported QOL analysis shows that ultra-hypofractionation was as well tolerated as conventional fractionation up to 6 years after completion of treatment. These findings support the use of ultra-hypofractionation radiotherapy for intermediate-to-high-risk prostate cancer.

Small cell lung cancer (SCLC) is characterized by rapid growth and high metastatic capacity. It has strong epidemiologic and biologic links to tobacco carcinogens. Although the majority of SCLCs exhibit neuroendocrine features, an important subset of tumors lacks these properties. Genomic profiling of SCLC reveals genetic instability, almost universal inactivation of the tumor suppressor genes TP53 and RB1, and a high mutation burden. Because of early metastasis, only a small fraction of patients are amenable to curative-intent lung resection, and these individuals require adjuvant platinum-etoposide chemotherapy. Therefore, the vast majority of patients are currently being treated with chemoradiation with or without immunotherapy. In patients with disease confined to the chest, standard therapy includes thoracic radiotherapy and concurrent platinum-etoposide chemotherapy. Patients with metastatic (extensive-stage) disease are treated with a combination of platinum-etoposide chemotherapy plus immunotherapy with an anti-programmed death-ligand 1 monoclonal antibody. Although SCLC is initially very responsive to platinum-based chemotherapy, these responses are transient because of the development of drug resistance. In recent years, the authors have witnessed an accelerating pace of biologic insights into the disease, leading to the redefinition of the SCLC classification scheme. This emerging knowledge of SCLC molecular subtypes has the potential to define unique therapeutic vulnerabilities. Synthesizing these new discoveries with the current knowledge of SCLC biology and clinical management may lead to unprecedented advances in SCLC patient care. Here, the authors present an overview of multimodal clinical approaches in SCLC, with a special focus on illuminating how recent advancements in SCLC research could accelerate clinical development.

The upcoming 5th edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours is part of an effort to hierarchically catalogue human cancers arising in various organ systems within a single relational database. This paper summarizes the new WHO classification scheme for myeloid and histiocytic/dendritic neoplasms and provides an overview of the principles and rationale underpinning changes from the prior edition. The definition and diagnosis of disease types continues to be based on multiple clinicopathologic parameters, but with refinement of diagnostic criteria and emphasis on therapeutically and/or prognostically actionable biomarkers. While a genetic basis for defining diseases is sought where possible, the classification strives to keep practical worldwide applicability in perspective. The result is an enhanced, contemporary, evidence-based classification of myeloid and histiocytic/dendritic neoplasms, rooted in molecular biology and an organizational structure that permits future scalability as new discoveries continue to inexorably inform future editions.

Retrospective studies have shown promising results using artificial intelligence (AI) to improve mammography screening accuracy and reduce screen-reading workload; however, to our knowledge, a randomised trial has not yet been conducted. We aimed to assess the clinical safety of an AI-supported screen-reading protocol compared with standard screen reading by radiologists following mammography. In this randomised, controlled, population-based trial, women aged 40–80 years eligible for mammography screening (including general screening with 1·5–2-year intervals and annual screening for those with moderate hereditary risk of breast cancer or a history of breast cancer) at four screening sites in Sweden were informed about the study as part of the screening invitation. Those who did not opt out were randomly allocated (1:1) to AI-supported screening (intervention group) or standard double reading without AI (control group). Screening examinations were automatically randomised by the Picture Archive and Communications System with a pseudo-random number generator after image acquisition. The participants and the radiographers acquiring the screening examinations, but not the radiologists reading the screening examinations, were masked to study group allocation. The AI system (Transpara version 1.7.0) provided an examination-based malignancy risk score on a 10-level scale that was used to triage screening examinations to single reading (score 1–9) or double reading (score 10), with AI risk scores (for all examinations) and computer-aided detection marks (for examinations with risk score 8–10) available to the radiologists doing the screen reading. Here we report the prespecified clinical safety analysis, to be done after 80 000 women were enrolled, to assess the secondary outcome measures of early screening performance (cancer detection rate, recall rate, false positive rate, positive predictive value [PPV] of recall, and type of cancer detected [invasive or in situ]) and screen-reading workload. Analyses were done in the modified intention-to-treat population (ie, all women randomly assigned to a group with one complete screening examination, excluding women recalled due to enlarged lymph nodes diagnosed with lymphoma). The lowest acceptable limit for safety in the intervention group was a cancer detection rate of more than 3 per 1000 participants screened. The trial is registered with ClinicalTrials.gov, NCT04838756, and is closed to accrual; follow-up is ongoing to assess the primary endpoint of the trial, interval cancer rate. Between April 12, 2021, and July 28, 2022, 80 033 women were randomly assigned to AI-supported screening (n=40 003) or double reading without AI (n=40 030). 13 women were excluded from the analysis. The median age was 54·0 years (IQR 46·7–63·9). Race and ethnicity data were not collected. AI-supported screening among 39 996 participants resulted in 244 screen-detected cancers, 861 recalls, and a total of 46 345 screen readings. Standard screening among 40 024 participants resulted in 203 screen-detected cancers, 817 recalls, and a total of 83 231 screen readings. Cancer detection rates were 6·1 (95% CI 5·4–6·9) per 1000 screened participants in the intervention group, above the lowest acceptable limit for safety, and 5·1 (4·4–5·8) per 1000 in the control group—a ratio of 1·2 (95% CI 1·0–1·5; p=0·052). Recall rates were 2·2% (95% CI 2·0–2·3) in the intervention group and 2·0% (1·9–2·2) in the control group. The false positive rate was 1·5% (95% CI 1·4–1·7) in both groups. The PPV of recall was 28·3% (95% CI 25·3–31·5) in the intervention group and 24·8% (21·9–28·0) in the control group. In the intervention group, 184 (75%) of 244 cancers detected were invasive and 60 (25%) were in situ; in the control group, 165 (81%) of 203 cancers were invasive and 38 (19%) were in situ. The screen-reading workload was reduced by 44·3% using AI. AI-supported mammography screening resulted in a similar cancer detection rate compared with standard double reading, with a substantially lower screen-reading workload, indicating that the use of AI in mammography screening is safe. The trial was thus not halted and the primary endpoint of interval cancer rate will be assessed in 100 000 enrolled participants after 2-years of follow up. Swedish Cancer Society, Confederation of Regional Cancer Centres, and the Swedish governmental funding for clinical research (ALF).

Tyrosine kinase inhibitors (TKIs) have improved the survival of patients with chronic myeloid leukaemia. Many patients have deep molecular responses, a prerequisite for TKI therapy discontinuation. We aimed to define precise conditions for stopping treatment. In this prospective, non-randomised trial, we enrolled patients with chronic myeloid leukaemia at 61 European centres in 11 countries. Eligible patients had chronic-phase chronic myeloid leukaemia, had received any TKI for at least 3 years (without treatment failure according to European LeukemiaNet [ELN] recommendations), and had a confirmed deep molecular response for at least 1 year. The primary endpoint was molecular relapse-free survival, defined by loss of major molecular response (MMR; >0·1% BCR-ABL1 on the International Scale) and assessed in all patients with at least one molecular result. Secondary endpoints were a prognostic analysis of factors affecting maintenance of MMR at 6 months in learning and validation samples and the cost impact of stopping TKI therapy. We considered loss of haematological response, progress to accelerated-phase chronic myeloid leukaemia, or blast crisis as serious adverse events. This study presents the results of the prespecified interim analysis, which was done after the 6-month molecular relapse-free survival status was known for 200 patients. The study is ongoing and is registered with ClinicalTrials.gov, number NCT01596114. Between May 30, 2012, and Dec 3, 2014, we assessed 868 patients with chronic myeloid leukaemia for eligibility, of whom 758 were enrolled. Median follow-up of the 755 patients evaluable for molecular response was 27 months (IQR 21–34). Molecular relapse-free survival for these patients was 61% (95% CI 57–64) at 6 months and 50% (46–54) at 24 months. Of these 755 patients, 371 (49%) lost MMR after TKI discontinuation, four (1%) died while in MMR for reasons unrelated to chronic myeloid leukaemia (myocardial infarction, lung cancer, renal cancer, and heart failure), and 13 (2%) restarted TKI therapy while in MMR. A further six (1%) patients died in chronic-phase chronic myeloid leukaemia after loss of MMR and re-initiation of TKI therapy for reasons unrelated to chronic myeloid leukaemia, and two (<1%) patients lost MMR despite restarting TKI therapy. In the prognostic analysis in 405 patients who received imatinib as first-line treatment (learning sample), longer treatment duration (odds ratio [OR] per year 1·14 [95% CI 1·05–1·23]; p=0·0010) and longer deep molecular response durations (1·13 [1·04–1·23]; p=0·0032) were associated with increasing probability of MMR maintenance at 6 months. The OR for deep molecular response duration was replicated in the validation sample consisting of 171 patients treated with any TKI as first-line treatment, although the association was not significant (1·13 [0·98–1·29]; p=0·08). TKI discontinuation was associated with substantial cost savings (an estimated €22 million). No serious adverse events were reported. Patients with chronic myeloid leukaemia who have achieved deep molecular responses have good molecular relapse-free survival. Such patients should be considered for TKI discontinuation, particularly those who have been in deep molecular response for a long time. Stopping treatment could spare patients from treatment-induced side-effects and reduce health expenditure. ELN Foundation and France National Cancer Institute.

Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging—Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale. In this international, paired, non-inferiority, confirmatory study, we trained and externally validated an AI system (developed within an international consortium) for detecting Gleason grade group 2 or greater cancers using a retrospective cohort of 10 207 MRI examinations from 9129 patients. Of these examinations, 9207 cases from three centres (11 sites) based in the Netherlands were used for training and tuning, and 1000 cases from four centres (12 sites) based in the Netherlands and Norway were used for testing. In parallel, we facilitated a multireader, multicase observer study with 62 radiologists (45 centres in 20 countries; median 7 [IQR 5–10] years of experience in reading prostate MRI) using PI-RADS (2.1) on 400 paired MRI examinations from the testing cohort. Primary endpoints were the sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) of the AI system in comparison with that of all readers using PI-RADS (2.1) and in comparison with that of the historical radiology readings made during multidisciplinary routine practice (ie, the standard of care with the aid of patient history and peer consultation). Histopathology and at least 3 years (median 5 [IQR 4–6] years) of follow-up were used to establish the reference standard. The statistical analysis plan was prespecified with a primary hypothesis of non-inferiority (considering a margin of 0·05) and a secondary hypothesis of superiority towards the AI system, if non-inferiority was confirmed. This study was registered at ClinicalTrials.gov, NCT05489341. Of the 10 207 examinations included from Jan 1, 2012, through Dec 31, 2021, 2440 cases had histologically confirmed Gleason grade group 2 or greater prostate cancer. In the subset of 400 testing cases in which the AI system was compared with the radiologists participating in the reader study, the AI system showed a statistically superior and non-inferior AUROC of 0·91 (95% CI 0·87–0·94; p<0·0001), in comparison to the pool of 62 radiologists with an AUROC of 0·86 (0·83–0·89), with a lower boundary of the two-sided 95% Wald CI for the difference in AUROC of 0·02. At the mean PI-RADS 3 or greater operating point of all readers, the AI system detected 6·8% more cases with Gleason grade group 2 or greater cancers at the same specificity (57·7%, 95% CI 51·6–63·3), or 50·4% fewer false-positive results and 20·0% fewer cases with Gleason grade group 1 cancers at the same sensitivity (89·4%, 95% CI 85·3–92·9). In all 1000 testing cases where the AI system was compared with the radiology readings made during multidisciplinary practice, non-inferiority was not confirmed, as the AI system showed lower specificity (68·9% [95% CI 65·3–72·4] vs 69·0% [65·5–72·5]) at the same sensitivity (96·1%, 94·0–98·2) as the PI-RADS 3 or greater operating point. The lower boundary of the two-sided 95% Wald CI for the difference in specificity (−0·04) was greater than the non-inferiority margin (−0·05) and a p value below the significance threshold was reached (p<0·001). An AI system was superior to radiologists using PI-RADS (2.1), on average, at detecting clinically significant prostate cancer and comparable to the standard of care. Such a system shows the potential to be a supportive tool within a primary diagnostic setting, with several associated benefits for patients and radiologists. Prospective validation is needed to test clinical applicability of this system. Health~Holland and EU Horizon 2020.

Breast cancer risk has been attributed to variation in many genes, and gene panels for clinical testing are correspondingly large. But how much risk can be reliably attributed to variation in specific genes? This large study provides answers.

In response to major changes in diagnostic algorithms and the publication of mature results from various large clinical trials, the European Association of Neuro-Oncology (EANO) recognized the need to provide updated guidelines for the diagnosis and management of adult patients with diffuse gliomas. Through these evidence-based guidelines, a task force of EANO provides recommendations for the diagnosis, treatment and follow-up of adult patients with diffuse gliomas. The diagnostic component is based on the 2016 update of the WHO Classification of Tumors of the Central Nervous System and the subsequent recommendations of the Consortium to Inform Molecular and Practical Approaches to CNS Tumour Taxonomy — Not Officially WHO (cIMPACT-NOW). With regard to therapy, we formulated recommendations based on the results from the latest practice-changing clinical trials and also provide guidance for neuropathological and neuroradiological assessment. In these guidelines, we define the role of the major treatment modalities of surgery, radiotherapy and systemic pharmacotherapy, covering current advances and cognizant that unnecessary interventions and expenses should be avoided. This document is intended to be a source of reference for professionals involved in the management of adult patients with diffuse gliomas, for patients and caregivers, and for health-care providers.Herein, the European Association of Neuro-Oncology (EANO) provides recommendations for the diagnosis, treatment and follow-up of adult patients with diffuse gliomas. These evidence-based guidelines incorporate major changes in diagnostic algorithms based on the 2016 update of the WHO Classification of Tumors of the Central Nervous System as well as on evidence from recent large clinical trials.

Although pembrolizumab has appeared to be more effective than chemotherapy in patients with lung cancer whose tumors had at least 50% PD-L1–positive cells, nivolumab was not as effective as chemotherapy in patients with lung cancer whose tumors had PD-L1 expression of at least 5%. For the past two decades, platinum-based combination chemotherapy has been the standard-of-care, first-line treatment for patients with advanced non–small-cell lung cancer (NSCLC) without mutations that were sensitive to targeted therapy. 1 , 2 However, chemotherapy has provided only a moderate benefit, with a limited safety profile. In phase 3 clinical trials, the median progression-free survival with platinum-based chemotherapy was 4 to 6 months, and the median overall survival was 10 to 13 months. 3 – 8 In two phase 3 trials, nivolumab, a programmed death 1 (PD-1) immune-checkpoint–inhibitor antibody, resulted in significantly longer overall survival than docetaxel among patients with metastatic NSCLC who had . . .

BACKGROUNDIdentifying factors conferring responses to therapy in cancer is critical to select the best treatment for patients. For immune checkpoint inhibition (ICI) therapy, mounting evidence suggests that the gut microbiome can determine patient treatment outcomes. However, the extent to which gut microbial features are applicable across different patient cohorts has not been extensively explored.METHODSWe performed a meta-analysis of 4 published shotgun metagenomic studies (Ntot = 130 patients) investigating differential microbiome composition and imputed metabolic function between responders and nonresponders to ICI.RESULTSOur analysis identified both known microbial features enriched in responders, such as Faecalibacterium as the prevailing taxa, as well as additional features, including overrepresentation of Barnesiella intestinihominis and the components of vitamin B metabolism. A classifier designed to predict responders based on these features identified responders in an independent cohort of 27 patients with the area under the receiver operating characteristic curve of 0.625 (95% CI: 0.348-0.899) and was predictive of prognosis (HR = 0.35, P = 0.081).CONCLUSIONThese results suggest the existence of a fecal microbiome signature inherent across responders that may be exploited for diagnostic or therapeutic purposes.FUNDINGThis work was funded by the Knut and Alice Wallenberg Foundation, BioGaia AB, and Cancerfonden.