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RIVM rapport:Every year, RIVM produces maps that show how much nitrogen is deposited in the Netherlands. We refer to this as nitrogen deposition. RIVM determines the nitrogen deposition by combining model calculations with measurements. These model calculations are necessary because measurements cannot be performed everywhere in the Netherlands. The deposition is influenced by the weather, the roughness of the terrain and characteristics of the vegetation. These factors give rise to a degree of uncertainty. In this technical report, RIVM describes how the uncertainties in terms of deposition levels are derived. In terms of degree, the uncertainties are similar to earlier estimates in 2004 and 2010, but they are now better underpinned. The uncertainty in a calculated deposition level is expressed as the probability of the calculated level deviating from the actual level. On the national scale, the probability that the calculated level deviates by between less than 20% and up to 30% from the actual level is considerable (95%). For specific areas in the Netherlands, there is a considerable probability (95%) that the calculated level deviates by between less than 60% and up to 70% from the actual level. This latter uncertainty applies when the deposition is calculated for a very small area, such as a hectare or a square kilometre. The degree of uncertainty of to the national nitrogen deposition is lower because uncertainties in the processes affecting deposition average out on the national scale. The results also show the largest contributors to the uncertainties in the overall nitrogen deposition. The most important factor in this regard is the uncertainty in the dry deposition, which entails nitrogen depositing on soil or vegetation directly from the air. There can be considerable variation from area to area and there is insufficient information to quantify this process., Elk jaar maakt het RIVM kaarten die aangeven hoeveel stikstof in Nederland op de bodem neerslaat. Dit noemen we stikstofdepositie. Het RIVM bepaalt de stikstofdepositie door modelberekeningen met metingen te combineren. Modelberekeningen zijn nodig omdat niet overal in Nederland kan worden gemeten. Het weer, de ruwheid van het land en eigenschappen van de begroeiing beïnvloeden de depositie en zorgen voor een bepaalde onzekerheid. In dit technische rapport beschrijft het RIVM hoe de onzekerheden in de depositiewaarden worden bepaald. De grootte van de onzekerheden zijn vergelijkbaar met de eerdere schattingen uit 2004 en 2010, maar zijn nu beter onderbouwd. De onzekerheid in de berekende depositiewaarde drukken we uit in de kans dat de berekende waarde een bepaalde afwijking heeft van de werkelijke waarde. Landelijk gezien is de kans groot (95 procent betrouwbaarheidsinterval) dat de berekende waarde minder dan 30 procent afwijkt van de werkelijke waarde. Op een specifieke locatie in Nederland is de kans groot (95 procent betrouwbaarheidsinterval) dat de berekende waarde minder dan 70 procent afwijkt van de werkelijke waarde. Deze onzekerheid geldt wanneer de depositie wordt berekend voor een heel klein gebied, zoals een hectare of een vierkante kilometer. De kleinere onzekerheid in de landelijke stikstofdepositie komt omdat onzekerheden in processen die invloed hebben op de depositie, op landelijke schaal uitmiddelen. De onzekerheden hebben geen betrekking op berekeningen voor specifieke projecten maar uitsluitend voor de totale depositie. De resultaten laten ook zien waar de grootste onzekerheden in de totale stikstofdepositie door komen. De onzekerheid in de droge depositie is daar het belangrijkste onderdeel van. Bij droge depositie komt stikstof direct via de lucht op de bodem of in de vegetatie terecht. De hoeveelheid kan van plek tot plek sterk verschillen en er is weinig informatie beschikbaar om dit proces te kwantificeren.

Background: In the absence of prognostic biomarkers, most patients with early-stage triple-negative breast cancer (eTNBC) are treated with combination chemotherapy. The identification of biomarkers to select patients for whom treatment de-escalation or escalation could be considered remains an unmet need. We evaluated the prognostic value of histopathologic traits in a unique cohort of young, (neo)adjuvant chemotherapy-naïve patients with early-stage (stage I or II), node-negative TNBC and long-term follow-up, in relation to stromal tumor-infiltrating lymphocytes (sTILs) for which the prognostic value was recently reported. Materials and methods: We studied all 485 patients with node-negative eTNBC from the population-based PARADIGM cohort which selected women aged <40 years diagnosed between 1989 and 2000. None of the patients had received (neo)adjuvant chemotherapy according to standard practice at the time. Associations between histopathologic traits and breast cancer-specific survival (BCSS) were analyzed with Cox proportional hazard models. Results: With a median follow-up of 20.0 years, an independent prognostic value for BCSS was observed for lymphovascular invasion (LVI) [adjusted (adj.) hazard ratio (HR) 2.35, 95% confidence interval (CI) 1.49-3.69], fibrotic focus (adj. HR 1.61, 95% CI 1.09-2.37) and sTILs (per 10% increment adj. HR 0.75, 95% CI 0.69-0.82). In the sTILs <30% subgroup, the presence of LVI resulted in a higher cumulative incidence of breast cancer death (at 20 years, 58%; 95% CI 41% to 72%) compared with when LVI was absent (at 20 years, 32%; 95% CI 26% to 39%). In the ≥75% sTILs subgroup, the presence of LVI might be associated with poor survival (HR 11.45, 95% CI 0.71-182.36, two deaths). We confirm the lack of prognostic value of androgen receptor expression and human epidermal growth factor receptor 2 -low status. Conclusions: sTILs, LVI and fibrotic focus provide independent prognostic information in young women with node-negat

01 januari 2023, Item does not contain fulltext, PURPOSE: We aimed to compare (1) treatments and time intervals between treatments of breast cancer patients diagnosed during and before the COVID-19 pandemic, and (2) the number of treatments started during and before the pandemic. METHODS: Women were selected from the Netherlands Cancer Registry. For aim one, odds ratios (OR) and 95% confidence intervals (95%CI) were calculated to compare the treatment of women diagnosed within four periods of 2020: pre-COVID (weeks 1-8), transition (weeks 9-12), lockdown (weeks 13-17), and care restart (weeks 18-26), with data from 2018/2019 as reference. Wilcoxon rank-sums test was used to compare treatment intervals, using a two-sided p-value < 0.05. For aim two, number of treatments started per week in 2020 was compared with 2018/2019. RESULTS: We selected 34,097 women for aim one. Compared to 2018/2019, neo-adjuvant chemotherapy was less likely for stage I (OR 0.24, 95%CI 0.11-0.53), stage II (OR 0.63, 95%CI 0.47-0.86), and hormone receptor+/HER2- tumors (OR 0.55, 95%CI 0.41-0.75) diagnosed during transition. Time between diagnosis and first treatment decreased for patients diagnosed during lockdown with a stage I (p < 0.01), II (p < 0.01) or III tumor (p = 0.01). We selected 30,002 women for aim two. The number of neo-adjuvant endocrine therapies and surgeries starting in week 14, 2020, increased by 339% and 18%, respectively. The number of adjuvant chemotherapies decreased by 42% in week 15 and increased by 44% in week 22. CONCLUSION: The pandemic and subsequently altered treatment recommendations affected multiple aspects of the breast cancer treatment strategy and the number of treatments started per week.

Contains fulltext : 296655.pdf (Publisher’s version ) (Open Access), BACKGROUND: Ductal carcinoma in situ (DCIS) can progress to invasive breast cancer (IBC), but most DCIS lesions remain indolent. However, guidelines recommend surgery, often supplemented by radiotherapy. This implies overtreatment of indolent DCIS. The non-randomised patient preference LORD-trial tests whether active surveillance (AS) for low-risk DCIS is safe, by giving women with low-risk DCIS a choice between AS and conventional treatment (CT). Here, we aim to describe how participants are distributed among both trial arms, identify their motives for their preference, and assess factors associated with their choice. METHODS: Data were extracted from baseline questionnaires. Descriptive statistics were used to assess the distribution and characteristics of participants; thematic analyses to extract self-reported reasons for the choice of trial arm, and multivariable logistic regression analyses to investigate associations between patient characteristics and chosen trial arm. RESULTS: Of 377 women included, 76% chose AS and 24% CT. Most frequently cited reasons for AS were "treatment is not (yet) necessary" (59%) and trust in the AS-plan (39%). Reasons for CT were cancer worry (51%) and perceived certainty (29%). Women opting for AS more often had lower educational levels (OR 0.45; 95% confidence interval [CI], 0.22-0.93) and more often reported experiencing shared decision making (OR 2.71; 95% CI, 1.37-5.37) than women choosing CT. CONCLUSION: The LORD-trial is the first to offer women with low-risk DCIS a choice between CT and AS. Most women opted for AS and reported high levels of trust in the safety of AS. Their preferences highlight the necessity to establish the safety of AS for low-risk DCIS.

Item does not contain fulltext, BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict treatment response before administering the therapy. METHODS: In this retrospective study, we developed hypothesis-driven interpretable biomarkers based on deep learning, to predict the pathological complete response (pCR, i.e., the absence of tumor cells in the surgical resection specimens) to neoadjuvant chemotherapy solely using digital pathology H&E images of pre-treatment breast biopsies. Our approach consists of two steps: First, we use deep learning to characterize aspects of the tumor micro-environment by detecting mitoses and segmenting tissue into several morphology compartments including tumor, lymphocytes and stroma. Second, we derive computational biomarkers from the segmentation and detection output to encode slide-level relationships of components of the tumor microenvironment, such as tumor and mitoses, stroma, and tumor infiltrating lymphocytes (TILs). RESULTS: We developed and evaluated our method on slides from n = 721 patients from three European medical centers with triple-negative and Luminal B breast cancers and performed external independent validation on n = 126 patients from a public dataset. We report the predictive value of the investigated biomarkers for predicting pCR with areas under the receiver operating characteristic curve between 0.66 and 0.88 across the tested cohorts. CONCLUSION: The proposed computational biomarkers predict pCR, but will require more evaluation and finetuning for clinical application. Our results further corroborate the potential role of deep learning to automate TILs quantification, and their predictive value in breast cancer neoadjuvant treatment planning, along with automated mitoses quantification. We made our method publicly available to extract segmentation-bas

Contains fulltext : 299968.pdf (Publisher’s version ) (Open Access), BACKGROUND: Comparing the impact of the COVID-19 pandemic on the incidence of newly diagnosed breast tumors and their tumor stage between the Netherlands and Norway will help us understand the effect of differences in governmental and social reactions towards the pandemic. METHODS: Women newly diagnosed with breast cancer in 2017-2021 were selected from the Netherlands Cancer Registry and the Cancer Registry of Norway. The crude breast cancer incidence rate (tumors per 100,000 women) during the first (March-September 2020), second (October 2020-April 2021), and Delta COVID-19 wave (May-December 2021) was compared with the incidence rate in the corresponding periods in 2017, 2018, and 2019. Incidence rates were stratified by age group, method of detection, and clinical tumor stage. RESULTS: During the first wave breast cancer incidence declined to a larger extent in the Netherlands than in Norway (27.7% vs. 17.2% decrease, respectively). In both countries, incidence decreased in women eligible for screening. In the Netherlands, incidence also decreased in women not eligible for screening. During the second wave an increase in the incidence of stage IV tumors in women aged 50-69 years was seen in the Netherlands. During the Delta wave an increase in overall incidence and incidence of stage I tumors was seen in Norway. CONCLUSION: Alterations in breast cancer incidence and tumor stage seem related to a combined effect of the suspension of the screening program, health care avoidance due to the severity of the pandemic, and other unknown factors., 01 december 2023

In this technical report, RIVM describes how the uncertainties in terms of deposition levels are derived. In terms of degree, the uncertainties are similar to earlier estimates in 2004 and 2010, but they are now better underpinned.

RIVM rapport:Vanuit het terrein van Tata Steel Nederland (TSN) worden verschillende chemische stoffen uitgestoten. Het RIVM heeft uitgezocht in hoeverre de huidige uitstoot van verschillende van deze stoffen naar de lucht effect heeft op de gezondheid van omwonenden. Dit is gedaan door de effecten van meerdere stoffen en hinder door stof, geluid en stank in samenhang te bekijken. Het onderzoek bevestigt dat de uitstoot van het Tata Steel-terrein bijdraagt aan de hoeveelheid fijnstof, stikstofdioxide, PAK(Polycyclische Aromatische Koolwaterstoffen ) en metalen in de directe leefomgeving. Vooral de uitstoot van fijnstof, stikstofoxiden en de hinder door stof, stank en geluid vergroten de kans op gezondheidseffecten. Omwonenden hebben hierdoor een iets grotere kans op astma, longkanker en om eerder te overlijden. De kans op effecten is het grootst in Wijk en Zee en neemt af naarmate mensen verder weg wonen van het Tata Steel terrein. Naar verwachting leven bewoners van Wijk aan Zee gemiddeld 2,5 maand korter door de blootstelling aan fijnstof en stikstofdioxide uitgestoten vanaf het Tata Steel-terrein. Daarnaast leidt de uitstoot tot een grotere kans op longkanker. We hebben berekend dat ongeveer 4 procent van toekomstige gevallen van longkanker in Wijk aan Zee is toe te schrijven aan de huidige uitstoot van fijnstof van het TSN-terrein. De blootstelling aan stikstofdioxide vergroot de kans op astma bij kinderen. Ook hierbij is het effect het grootst in Wijk aan Zee: ongeveer 3 procent van toekomstige gevallen hangen met de huidige uitstoot samen. Een groot deel van de bewoners van de IJmond ervaart hinder door stof, stank en geluid afkomstig van bedrijven. In Wijk aan Zee loopt het percentage op tot 80 procent. Bewoners melden hierbij slaapverstoring. Ook maken zij zich zorgen over hun gezondheid door de nabijheid van het industrieterrein. Hinder kan gezondheidseffecten veroorzaken zoals stress en hart- en vaatziekten. De meeste winst voor de gezondheid is te bereiken door de uits, The Tata Steel Netherlands (TSN) site is the source of a variety of chemical emissions. RIVM has investigated the extent to which several of these substances – at the levels they are currently being emitted into the air – affect the health of local residents. This was done by examining the effects of multiple substances and dust, noise and odour nuisance, all considered in conjunction with one another. The research confirmed that the emissions from the Tata Steel site contribute to the quantities of particulate matter, nitrogen dioxide, polycyclic aromatic hydrocarbons (PAHs) and metals in the immediate surroundings. In particular, the emissions of particulate matter and nitrogen dioxide and dust, odour and noise nuisance increases the likelihood of adverse health effects. As a result, local residents are at a slightly elevated risk of asthma, lung cancer and premature death. The likelihood of these effects is highest in Wijk aan Zee and decreases the further away from the Tata Steel site. Due to exposure to particulate matter and nitrogen dioxide emitted from the Tata Steel site, Wijk aan Zee residents have a life expectancy that is 2.5 months lower on average. The emissions also lead to an increased risk of lung cancer. We have calculated that approximately 4% of the future cases of lung cancer in Wijk aan Zee will be attributable to the current emissions of particulate matter from the Tata Steel site. The exposure to nitrogen dioxide increases the likelihood of asthma among children under the age of 18 in the surrounding area. Here, the effect is also greatest in Wijk aan Zee: around 3% of future cases will be associated with the current emissions. A large portion of people living in the IJmond region experience dust, odour and noise nuisance from industry. In Wijk aan Zee, the percentage can be as high as 80%. Residents have also reported sleep disturbance. In addition, they have concerns about their health in connection with the proximity to the industrial esta

Exploratory analyses of high-dose alkylating chemotherapy trials have suggested that BRCA1 or BRCA2-pathway altered (BRCA-altered) breast cancer might be particularly sensitive to this type of treatment. In this study, patients with BRCA-altered tumors who had received three initial courses of dose-dense doxorubicin and cyclophosphamide (ddAC), were randomized between a fourth ddAC course followed by high-dose carboplatin-thiotepa-cyclophosphamide or conventional chemotherapy (initially ddAC only or ddAC-capecitabine/decetaxel [CD] depending on MRI response, after amendment ddAC-carboplatin/paclitaxel [CP] for everyone). The primary endpoint was the neoadjuvant response index (NRI). Secondary endpoints included recurrence-free survival (RFS) and overall survival (OS). In total, 122 patients were randomized. No difference in NRI-score distribution (p = 0.41) was found. A statistically non-significant RFS difference was found (HR 0.54; 95% CI 0.23–1.25; p = 0.15). Exploratory RFS analyses showed benefit in stage III (n = 35; HR 0.16; 95% CI 0.03–0.75), but not stage II (n = 86; HR 1.00; 95% CI 0.30–3.30) patients. For stage III, 4-year RFS was 46% (95% CI 24–87%), 71% (95% CI 48–100%) and 88% (95% CI 74–100%), for ddAC/ddAC-CD, ddAC-CP and high-dose chemotherapy, respectively. No significant differences were found between high-dose and conventional chemotherapy in stage II-III, triple-negative, BRCA-altered breast cancer patients. Further research is needed to establish if there are patients with stage III, triple negative BRCA-altered breast cancer for whom outcomes can be improved with high-dose alkylating chemotherapy or whether the current standard neoadjuvant therapy including carboplatin and an immune checkpoint inhibitor is sufficient. Trial Registration: NCT01057069.

RIVM rapport:In 2021 concludeerde de Gezondheidsraad dat er nog weinig bekend is over de risico’s voor de gezondheid van de kleinste deeltjes fijnstof (ultrafijnstof, UFP(ultrafine particles (ultrafijne deeltjes))) in de buitenlucht. De raad adviseerde ultrafijnstof structureel te gaan meten en modelleren. Daarmee kan worden bepaald hoeveel ultrafijnstof de Nederlandse bevolking via de lucht inademt. Het ministerie van Infrastructuur en Waterstaat (IenW(Infrastructuur en Waterstaat)) heeft het RIVM gevraagd of het mogelijk is om metingen van ultrafijnstof in het landelijk meetnet voor luchtkwaliteit op te nemen. Het RIVM denkt dat het kan en gaat meetstations inrichten om er ervaring mee op te doen. Het is nog wel te vroeg om een groot meetnet met veel meetpunten op te zetten. Dat komt omdat er nog veel kennis over UFP ontbreekt. Ultrafijnstof is een mengsel van extreem kleine deeltjes (kleiner dan 0,1 micrometer) die verschillen in grootte, van verschillende bronnen komen en verschillende stoffen bevat. Daardoor kan de concentratie niet zoals fijnstof worden gemeten, maar moeten de deeltjes worden geteld. Het RIVM stelt voor om op (minimaal) zeven vaste stations de aantallen ultrafijne deeltjes te meten en op enkele stations ook de grootte van de deeltjes. Kennis over de grootte van de deeltjes is nodig om meer inzicht in gezondheidseffecten te krijgen. Daar is nog weinig over bekend. Om een beeld van de blootstelling aan UFP in heel Nederland te krijgen, wordt deze naast de metingen berekend met rekenmodellen. Het is namelijk te duur om veel meetpunten te plaatsen. Met genoeg meetgegevens is het mogelijk om in Nederland verschillen in de concentraties te berekenen en op kaarten aan te geven. Voor dit onderzoek heeft het RIVM gesproken met experts in België en Groot-Brittannië en deskundigen van de regionale meetnetten over instrumenten en toekomstige plannen. Daarnaast is gezondheidsdeskundigen in Nederland gevraagd wat hun wensen zijn over het meten en modelleren van UFP. Op, In 2021, the Health Council of the Netherlands found that much remains unknown about the health risks associated with airborne ultrafine particles (UFP). The Health Council recommended the systematic measuring and modelling of ultrafine particles. This will make it possible to determine the amount of airborne ultrafine particles inhaled by the Dutch population. The Ministry of Infrastructure and Water Management has asked RIVM whether it is possible to have these ultrafine particle measurements conducted by the National Air Quality Monitoring Network. RIVM believes this can be done and will set up monitoring stations in order to gain the necessary experience. Because of the scant knowledge regarding UFP, it is too early to set up a large-scale monitoring network with a high number of monitoring stations. The term ‘ultrafine particles’ refers to a mixture of extremely small particles (smaller than 0.1 micrometre) that vary in size, origin and composition. This makes it impossible to measure their concentration in the air, as can be done for fine particles. Instead, the number of ultrafine particles must be measured. RIVM proposes to set up (at least) seven fixed monitoring stations to measure the number of ultrafine particles and a few mobile stations to measure their size. Knowledge about the size of the particles is required to gain further insight into their health effects. That knowledge is currently largely absent. The mobile monitoring stations will also detect the provenance of UFP emissions. To get a clear picture of the exposure of the Dutch population to UFP, the measurements will be supplemented with calculations derived from computer modelling. The reason for using this approach is that it is too expensive to set up a large number of monitoring stations. Given sufficient measurement data, it will be possible to estimate the number of ultrafine particles over the Netherlands and indicate these on a map. To prepare for this investigation, RIVM held discussi

Voor het uitvoeren van modelberekeningen met betrekking tot de grondwaterstroming in de onverzadigde bodem is kennis van de bodemfysische karakteristieken (pF-curve en doorlatendheid) vereist. Hiervoor wordt in Nederland gewoonlijk de Staringreeks gebruikt. Deze is gebaseerd op de bodemkaart 1:50000. Met behulp van de Staringreeks is de Bodemfysische Eenheden Kaart (BOFEK) ontwikkeld voor toepassingen op landelijke schaal. Maar is een dergelijk classificatiesysteem wel geschikt voor accurate modelberekeningen? Dat hebben we onderzocht aan de hand van een paar eenvoudige voorbeelden.

BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

Background: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. Methods: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. Results: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. Conclusion: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.