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OBJECTIVES: Ferric carboxymaltose (FCM) is increasingly used in the management of cancer-related anemia, yet it may cause hypophosphatemia. This retrospective study describes the incidence, evolution and risk factors of hypophosphatemia in a cohort of patients with solid tumors receiving FCM. METHODS: Serum phosphorus concentration was assessed longitudinally using a random intercepts model. The probability of developing hypophosphatemia, as graded by CTCAE version 4.0, was investigated using a multi-state model. Transition hazards were modeled non-parametrically and semi-parametrically by a Cox model. Causal marginal risk differences between baseline interventions on serum phosphorus and/or FCM dose were obtained via G-computation. RESULTS: In 174 ambulatory patients with solid tumors receiving FCM at two university hospitals between October 2020 and September 2021, the risk of developing moderate-to-severe hypophosphatemia was 36.0% (95% confidence interval (CI) 28.2-43.9%) and peaked within 16 days afterfirst FCM administration. The average duration of moderate-to-severe hypophosphatemia was 12.4 days. After adjustment for confounders, lower baseline serum phosphorus (adjusted hazard ratio (aHR) 0.88 per 0.1 mmol/L increase, 95% CI 0.79-0.98) and higher FCM dose (first dose: aHR 1.12 per 1 mg/kg increase, 95% CI 1.01-1.25; second dose: aHR 1.06 per 1 mg/kg increase, 95% CI 1.00-1.13) significantly increased the hazard of moderate-to-severe hypophosphatemia. CONCLUSION: Approximately one out of three ambulatory patients with solid tumors may develop moderate-to-severe hypophosphatemia after FCM administration. Baseline serum phosphorus and FCM dose may be modifiable risk factors that should be considered for intervention in order to mitigate the risk of hypophosphatemia.

Additional file 1: Survival outcomes. Table S1. Survival data. Table S2. univariate cox regression analysis of preoperative clinical and pathological features as prognostic factors for overall survival. Table S3. univariate cox regression analysis of preoperative clinical and pathological features as prognostic factors for disease free survival. Fig. S1. OS, DFS, PC and LC for the intention to treat group. Fig. S2. OS, DFS, PC and LC stratified according to FIGO 2009 (left) and FIGO 2018 (right).

Additional file 1: Supplementary Table 1. Patient registration rate, overall and specific.

Introduction: Extracellular vesicles (EV) in body fluids are extensively studied as potential biomarkers for numerous diseases. Major impediments of EV‐based biomarker discovery include the specificity and reproducibility of EV sample preparation. To tackle this, we present an automated liquid handling workstation for the density‐based separation of EV from human body fluids and compare its performance to manual handling by (in)experienced researchers. Methods: Variability in density‐based EV separation using manual versus automated liquid handling is first evaluated by spiking PBS with trackable recombinant extracellular vesicles (rEV) followed by the quantification of rEV recovery efficiency using fluorescent NTA and ELISA (Geeurickx et al., Nature Comm, 2019). Next, EV are separated from blood plasma and urine through the orthogonal implementation of size‐exclusion chromatography and manual or automated density‐gradient centrifugation as previously described (Dhondt et al., STAR Protoc, 2020; Tulkens et al., Nature Protoc, 2020). Variability, EV yield and purity are assessed by MS‐based proteomics and transmission electron microscopy. Results: Automated versus manual liquid handling significantly reduces variability in rEV recovery after density‐based separation (CVauto 11.6% vs CVman 26.4%), and significantly decreases variability in EV preparations obtained from blood plasma and urine. Indeed, the median CVauto for protein group quantification are between 17.2% (plasma) and 20.0% (urine), CVman,exp between 38.5% (plasma) and 22.6% (urine), and CVman,inexp between 43.2% (plasma) and 27.6% (urine). While retaining an equal EV yield compared to manual liquid handling, automation significantly diminishes the presence of contaminating abundant proteins in EV preparations, including lipoproteins in plasma (2‐fold decrease in ApoB) and uromodulin in urine (2.6‐fold decrease in THP). Summary/Conclusion: Automated liquid handling ensures EV separation from body fluids with high reproducibility and specificity.

Table S1. Relapse pattern in the entire cohort and neo-adjuvant chemoradiation group. Table S2. Univariate analysis of DSS. Table S3. Multivariate analysis of DSS. (DOCX 26 kb)

Oestrogen receptor positive early invasive breast cancer is a common disease in pre- and perimenopausal women. Adjuvant endocrine therapy is an essential part of its treatment. Until recently, premenopausal patients were uniformly treated with tamoxifen during fi ve years. Given the recent publication of large clinical trials showing a benefi t for other treatment regimens, the BSMO Breast Cancer Task Force met on the 6th of March, 2015, to propose common guidelines for adjuvant endocrine therapy for premenopausal patients. The members agreed that low-risk patients should be treated with fi ve to ten years of tamoxifen, while the highest-risk patients should be treated with exemestane or tamoxifen plus ovarian function suppression. Special attention should be given to patients less than 35 years at diagnosis: in this subgroup, exemestane plus ovarian function suppression is preferred to tamoxifen plus ovarian function suppression.

Background: Adipose tissue is a dynamic organ that secretes a plethora of molecules called adipokines. In breast cancer we find a unique situation were genetically changed cells (the cancer cells) are in close contact with adipocytes. Moreover, obesity is a known negative prognostic marker for postmenopausal breast cancer patients. We hypothesize that adipocyte-derived factors influence breast cancer progression. Materials and methods: Adipose tissue was collected from breast cancer patients undergoing a mastectomy. After macroscopic removal of blood vessels and connective tissue, the adipose tissue was carefully cut into 2-3mm3 pieces and were incubated in specific adipose-tissue culture medium. After 24h, the medium was collected and the quality was checked by determining the concentration of total proteins, leptin, adiponectin, TNFalpha and triglycerides. This conditioned medium of adipose tissue (CM AT) was used for in vitro experimentation with MCF-7 breast cancer cells. Results: Effect of AT on morphology and aggregation: when MCF-7 cells are grown in a culture flask, they tend to form round compact islands. Under influence of CM AT, the islands form sharp edges, the cells in an island can be counted individually and they show scattering. Importantly, despite the major changes in cellular morphology, CM AT removal rescued the compact island formation of MCF-7 cells. In the slow aggregation assay, cells treated with CM AT (and a subtherapeutic concentration of a neutralizing E-cadherin antibody) lost the ability to form compact aggregates. Furthermore, MCF-7 spheroids placed inside adipose tissue showed massive reorganization into an irregularly shaped mass. Effect of AT on proliferation: starting from an equal number of cells and counting them every 2 days, it became clear that MCF-7 cells with CM AT had a higher rate of proliferation than MCF-7 cells in control medium. This stimulation of proliferation was confirmed by cell cycle analysis which revealed a doubling of cells in the G2/M phase, and western blot which showed an upregulation of cyclin A and cyclin E, both positive regulators of the cell cycle. Effect of AT on invasion: a 24h collagen type I invasion assay revealed invasive characteristics of MCF-7 cells treated with CM AT while MCF-7 cells in control conditions are round and non-invasive. In contrast, a transwell collagen test over 14 days was not able to show MCF-7 cells invading the collagen gel under influence of CM AT. However, the growth pattern of MCF-7 cells on the collagen gel was clearly disorganised when compared with the control situation. Conclusion: These findings suggest that adipose tissue-derived factors exert a dramatic selective force on patterning, invasion and growth of MCF-7 breast cancer cells. Unraveling the mechanism behind these observations may provide vital information regarding the link between obesity and poor prognosis in postmenopausal breast cancer.

Immunotherapy; PARP inhibitors; Pembrolizumab Immunoteràpia; Inhibidors de PARP; Pembrolizumab Inmunoterapia; Inhibidores de PARP; Pembrolizumab Metastatic triple-negative breast cancer (mTNBC) is a poor prognostic disease with limited treatments and uncertain therapeutic algorithms. We performed a systematic review and multiple Bayesian network meta-analyses according to treatment line to establish an optimal therapeutic sequencing strategy for this lethal disease. We included 125 first-line trials (37,812 patients) and 33 s/further-lines trials (11,321 patients). The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rates (ORR), overall survival (OS) and safety, for first and further lines, separately. We also estimated separate treatment rankings for the first and subsequent lines according to each endpoint, based on (surface under the cumulative ranking curve) SUCRA values. No first-line treatment was associated with superior PFS and OS than paclitaxel ± bevacizumab. Platinum-based polychemotherapies were generally superior in terms of ORR, at the cost of higher toxicity.. PARP-inhibitors in germline-BRCA1/2-mutant patients, and immunotherapy + chemotherapy in PD-L1-positive mTNBC, performed similar to paclitaxel ± bevacizumab. In PD-L1-positive mTNBC, pembrolizumab + chemotherapy was better than atezolizumab + nab-paclitaxel in terms of OS according to SUCRA values. In second/further-lines, sacituzumab govitecan outperformed all other treatments on all endpoints, followed by PARP-inhibitors in germline-BRCA1/2-mutant tumors. Trastuzumab deruxtecan in HER2-low mTNBC performed similarly and was the best advanced-line treatment in terms of PFS and OS after sacituzumab govitecan, according to SUCRA values. Moreover, comparisons with sacituzumab govitecan, talazoparib and olaparib were not statistically significant. The most effective alternatives or candidates for subsequent lines were represented by nab-paclitaxel (in ORR), capecitabine (in PFS) and eribulin (in PFS and OS).

29 p. ill., Het Federaal Kenniscentrum voor de Gezondheidszorg (KCE) publiceert een set van 15 kwaliteitsindicatoren voor de behandeling van eierstokkanker. Dit maakt deel uit van een continu proces om de kwaliteit van de kankerzorg in België te verbeteren en is reeds met succes toegepast bij andere types kanker. De 15 indicatoren werden berekend voor alle ziekenhuizen, die een individueel feedbackrapport van de Stichting Kankerregister zullen ontvangen, zodat zij hun sterke en zwakke punten kunnen identificeren en waar nodig de zorg verbeteren. In een tweede deel toont de studie aan dat de kans van patiënten op overleven duidelijk hoger is in ziekenhuizen die elk jaar een groot aantal patiënten behandelen. Het KCE pleit er dan ook voor de behandeling van eierstokkanker in een beperkt aantal referentiecentra te concentreren. Bij de erkenning van deze referentiecentra mag het aantal behandelde patiënten zeker niet het enige criterium zijn. VOORWOORD 1 --  KERN-BOODSCHAPPEN 2 -- 1. CONTEXT EN DOELSTELLINGEN 7 -- 1.1. HET BELGISCH SYSTEEM TER VERBETERING VAN DE KWALITEIT VAN ZORG IN DE -- ONCOLOGIE 7 -- 1.2. EIERSTOKKANKER 8 -- 1.3. DOELSTELLINGEN VAN DEZE STUDIE 8 -- 2. GEGEVENS EN METHODEN 9 -- 2.1. IDENTIFICATIE EN SELECTIE VAN DE KWALITEITSINDICATOREN 9 -- 2.2. DOELPOPULATIE VAN DE STUDIE 9 -- 2.2.1. Gegevensbronnen 9 -- 2.2.2. Meer dan 5.000 patiënten in de studie opgenomen tussen 2014 en 2018 10 -- 2.2.3. Toegepaste behandelingen 11 -- 2.2.4. Andere kenmerken die in aanmerking werden genomen in de analyses 11 -- 2.2.5. Toewijzing van elke patiënte aan een ziekenhuis 11 -- 2.3. VALIDATIESTUDIE 12 -- 3. RESULTATEN VAN DE KWALITEITSINDICATOREN 12 -- 3.1. DIAGNOSE EN STADIËRING 14 -- 3.2. CHEMOTHERAPIE 16 -- 3.3. COMPLICATIES, STERFTE EN OVERLEVING 17 -- 4. INVLOED VAN HET ZIEKENHUISVOLUME OP DE RESULTATEN 18 -- 4.1. GROTE VERSNIPPERING VAN DE ZORG 18 -- 4.2. VERBAND TUSSEN HET ZIEKENHUISVOLUME VAN BEHANDELING EN DE OVERLEVING IN BELGIË 19 -- 4.3. VERBAND TUSSEN HET CHIRURGISCH VOLUME VAN HET ZIEKENHUIS EN DE OVERLEVING IN BELGIË 19 -- 4.4. LITERATUURSTUDIE 20 -- 5. CONCLUSIE 21 -- AANBEVELINGEN 24 -- REFERENTIES 28

29 p. ill., Le Centre fédéral d’Expertise des Soins de santé (KCE) publie un ensemble de 15 indicateurs de qualité pour la prise en charge du cancer de l’ovaire. Cette démarche s’inscrit dans un processus continu d’amélioration de la qualité des soins en oncologie en Belgique et a déjà été appliquée avec fruit pour d’autres types de cancers. Les résultats des 15 indicateurs ont été calculés au niveau national, et tous les hôpitaux recevront ensuite un rapport d'évaluation individuel envoyé par la Fondation Registre du Cancer. Cela leur permettra d'identifier leurs points forts et leurs points faibles et d'améliorer leurs pratiques si nécessaire. Dans une seconde partie, l’étude a démontré que les chances de survie sont nettement plus élevées dans les hôpitaux qui traitent un grand nombre de patientes chaque année. Le KCE plaide donc pour une concentration de la prise en charge du cancer de l’ovaire dans un nombre limité de centres de référence. La reconnaissance de ces centres de référence ne doit cependant pas se baser sur le seul nombre de patientes traitées. PRÉFACE 1 -- MESSAGES CLÉS 2 -- 1. CONTEXTE ET OBJECTIFS 6 -- 1.1. LE SYSTÈME BELGE D’AMÉLIORATION DE LA QUALITÉ DES SOINS EN ONCOLOGIE 6 -- 1.2. LE CANCER DE L’OVAIRE 7 -- 1.3. OBJECTIFS DE CETTE ÉTUDE 7 -- 2. DONNÉES ET MÉTHODES 8 -- 2.1. IDENTIFICATION ET SÉLECTION DES INDICATEURS DE QUALITÉ 8 -- 2.2. POPULATION CIBLE DE CETTE ÉTUDE 8 -- 2.2.1. Sources de données 8 -- 2.2.2. Plus de 5 000 patientes incluses entre 2014 et 2018 9 -- 2.2.3. Traitements administrés 10 -- 2.2.4. Autres caractéristiques prises en compte 10 -- 2.2.5. Assignation de chaque patiente à un hôpital 10 -- 2.3. ÉTUDE DE VALIDATION 10 -- 3. RÉSULTATS DES INDICATEURS DE QUALITÉ 11 -- 3.1. DIAGNOSTIC ET STADIFICATION 13 -- 3.2. CHIMIOTHÉRAPIE 14 -- 3.3. COMPLICATIONS, MORTALITÉ ET SURVIE 15 -- 4. IMPACT DU VOLUME HOSPITALIER SUR LES RÉSULTATS 16 -- 4.1. GRANDE DISPERSION DES SOINS EN BELGIQUE 16 -- 4.2. RELATION ENTRE LE VOLUME HOSPITALIER DE PRISE EN CHARGE THÉRAPEUTIQUE ET LA SURVIE EN BELGIQUE 17 -- 4.3. RELATION ENTRE LE VOLUME CHIRURGICAL HOSPITALIER ET LA SURVIE EN BELGIQUE 18 -- 4.4. REVUE DE LITTÉRATURE INTERNATIONALE 18 -- 5. CONCLUSION 19 -- RECOMMANDATIONS 22 -- RÉFÉRENCES 26

357 p. ill., SCIENTIFIC REPORT 23 -- 1 INTRODUCTION 23 -- 1.1 OVARIAN CANCER 24 -- 1.1.1 Background 24 -- 1.1.2 Epidemiology of ovarian cancer in Belgium 24 -- 1.2 DISPERSION OF CARE FOR OVARIAN CANCER IN BELGIUM 25 -- 1.3 MEASURING QUALITY 26 -- 2 OBJECTIVES AND SCOPE 27 -- 2.1 AIM OF THE STUDY 27 -- 2.2 SCOPE 27 -- 2.3 TARGET AUDIENCE 27 -- 3 METHODOLOGY 28 -- 3.1 STEP 1: IDENTIFICATION OF THE TARGET POPULATION: DATA SELECTION AND LINKAGE OF DATABASES 28 -- 3.1.1 Selection of the study population in the Belgian Cancer Registry database 28 -- 3.1.2 Linkage with health insurance data 30 -- 3.1.3 Vital status 31 -- 3.1.4 Pathology reports 31 -- 3.1.5 Data unavailable for assessment of quality indicators 31 -- 3.2 STEP 2: IDENTIFICATION AND SELECTION OF POSSIBLE QUALITY INDICATORS 31 -- 3.2.1 Identification of possible quality indicators 31 -- 3.2.2 Selection process and results 31 -- 3.2.3 Measurability of selected quality indicators 32 -- 3.2.4 Final selection of quality indicators to be fully elaborated 32 -- 3.3 STEP 3: OPERATIONALIZATION OF INDICATORS 34 -- 3.3.1 Technical fiches 35 -- 3.3.2 Defining diagnostic and therapeutic procedures 35 -- 3.3.3 Defining the treatment scheme of the patient 41 -- 3.3.4 Case-mix adjustment 41 -- 3.3.5 Statistical analysis 44 -- 3.4 STEP 4: ASSIGNMENT OF EACH PATIENT TO ONE CENTRE 47 -- 3.5 STEP 5: VALIDATION OF DIAGNOSTIC AND THERAPEUTIC DATA 50 -- 3.5.1 Introduction and methodology 50 -- 3.5.2 Results of the validation of the algorithm to assign each patient to one centre of first diagnosis and one centre of main treatment 51 -- 3.5.3 Validation of the patient and tumour characteristics and of diagnostic and therapeutic procedures 52 -- 3.5.4 Validation of the quality indicator results 56 -- 3.5.5 Conclusion 56 -- 4 CHARACTERISTICS OF THE STUDY COHORT 56 -- 4.1 BASELINE DEMOGRAPHICS AND TUMOUR CHARACTERISTICS 57 -- 4.2 MAIN DIAGNOSTIC PROCEDURES 57 -- 4.3 MAIN THERAPEUTIC PROCEDURES 58 -- 4.3.1 Surgical procedures 58 -- 4.3.2 Chemotherapy (including targeted therapy) 59 -- 4.3.3 Comprehensive treatment (TT01) 59 -- 4.3.4 Treatment schemes 59 -- 5 INDICATOR RESULTS 60 -- 5.1 QUALITY OF DIAGNOSIS AND STAGING IN EPITHELIAL OVARIAN CANCER 60 -- 5.1.1 Multidisciplinary team (MDT) meeting (DS01) 60 -- 5.1.2 Genetic testing (DS02) 62 -- 5.1.3 Cyto/histological diagnosis prior to starting chemotherapy (DS03) 65 -- 5.1.4 Minimal staging surgery (DS04) 67 -- 5.1.5 Abdomino-pelvic imaging prior to starting treatment (DS05) 70 -- 5.1.6 Lymph node removal in women with invasive I-IIA epithelial ovarian cancer (DS06) 72 -- 5.1.7 No lymphadenectomy in women with a borderline ovarian tumour (DS07) 74 -- 5.2 QUALITY OF TREATMENT IN EPITHELIAL OVARIAN CANCER 75 -- 5.2.1 Platinum-based chemotherapy, either in combination or as a single agent (CT01) 75 -- 5.2.2 Duration of platinum-based chemotherapy (CT02) 78 -- 5.2.3 Timeliness of chemotherapy (CT03) 82 -- 5.2.4 Timeliness of start of first treatment (TT02) 84 -- 5.2.5 Systemic treatment within 2 weeks of death (EOL) 86 -- 5.3 SAFETY OF CARE IN EPITHELIAL OVARIAN CANCER 88 -- 5.3.1 30-day post-operative complicated recovery (OS01) 88 -- 5.3.2 30-day post-operative mortality (OS02) 90 -- 5.4 1, 2 AND 5-YEAR OBSERVED AND RELATIVE SURVIVAL (OS03) 93 -- 5.5 ASSOCIATION BETWEEN HOSPITAL VOLUME AND OUTCOME 96 -- 5.5.1 Hospital main treatment volume and survival (VO01) 96 -- 5.5.2 Hospital surgical volume and outcome (VO02) 100 -- 5.5.3 Discussion 105 -- 6 STRENGHS AND LIMITATIONS 107 -- 7 CONCLUSIONS AND PERSPECTIVES FOR THE FUTURE 110 -- RECOMMENDATIONS 116 -- APPENDICES 119

37 p. ill., KEY MESSAGES 1 -- SHORT REPORT 3 -- 1. BACKGROUND 6 -- 1.1. QUALITY IMPROVEMENT INITIATIVES IN ONCOLOGY 6 -- 1.2. EPIDEMIOLOGY OF OVARIAN CANCER 6 -- 1.3. SCOPE 6 -- 1.4. AIM OF THE STUDY 7 -- 2. DATA AND METHODS 7 -- 2.1. IDENTIFICATION AND SELECTION OF QUALITY INDICATORS 7 -- 2.2. DATA SELECTION AND LINKAGE OF DATABASES 7 -- 2.3. DEFINITION OF SURGERY BASED ON PATHOLOGY REPORTS 8 -- 2.4. CASE-MIX ADJUSTMENT 8 -- 2.5. STATISTICAL ANALYSES 8 -- 2.6. ASSIGNMENT OF PATIENTS TO A CENTRE 9 -- 2.7. VALIDATION STUDY AND SUBSEQUENT DATA CHECKS 9 -- 3. QUALITY OF CARE FOR PATIENTS WITH EPITHELIAL OVARIAN CANCER 10 -- 3.1. BASELINE DEMOGRAPHICS AND TUMOUR CHARACTERISTICS 10 -- 3.2. MAIN THERAPEUTIC PROCEDURES 11 -- 3.3. RESULTS FOR 15 QUALITY INDICATORS 12 -- 3.3.1. Diagnosis and staging 14 -- 3.3.2. Treatment 16 -- 3.3.3. Safety of care – 30-day complicated recovery and mortality after surgery 18 -- 3.3.4. Survival after the diagnosis of epithelial ovarian cancer 19 -- 3.4. ASSOCIATION BETWEEN HOSPITAL VOLUME AND OUTCOMES 21 -- 3.4.1. Dispersion of care 21 -- 3.4.2. Hospital main treatment volume 22 -- 3.4.3. Hospital surgical volume 23 -- 3.4.4. Discussion 24 -- 4. STRENGTHS AND LIMITATIONS 25 -- 5. CONCLUSIONS AND PERSPECTIVES FOR THE FUTURE 27 -- RECOMMENDATIONS 30 -- REFERENCES 33