Acta Oncologica最新文献

Background and purpose: Low-dose CT screening of high-risk groups has been shown to reduce lung cancer mortality, and the European Council has therefore recommended that member states explore the feasibility and effectiveness of this approach. In this study, we evaluate the implementation of low-dose CT screening for lung cancer in a Swedish female population. Patient/material and methods: Women aged 54-74 years in the Southern Stockholm region were contacted via an electronic questionnaire. Individuals who met the same eligibility criteria as in the NELSON trial (a minimum smoking history of 15 pack-years) were invited. The screening consisted of a baseline low-dose computed tomography (LDCT) scan, with the option for a follow-up scan in cases with intermediate findings. Findings were managed in accordance with modified Fleischner Society guidelines.

Results: Between September 2022 and September 2024, 34,580 invitation letters were sent to randomly selected women aged 54-74 years 11,607 individuals (33.4%) completed the questionnaire, whereof 1,106 (10%) met the inclusion criteria. 990 (90%) individuals accepted the invitation and underwent a baseline low-dose CT scan. There were 152 intermediate and 55 positive scans at baseline, and additional eight positive scans at follow-up. Fifteen cases of Lung cancer were found, yielding a positive prediction value (PPV) of 24%. 87% of the lung cancers were in stage IA.

Interpretation: Organized lung cancer screening in a Swedish female population proved feasible, demonstrating a good participation rate, and a cancer detection rate consistent with findings from other major screening trials.

Background and purpose: Molecularly targeted cancer therapies challenge conventional health economic evaluation frameworks that are structured around tumour-specific indications, comparators, and trial designs. Existing models often rely on pooled estimates from heterogeneous early-phase evidence or single-indication analyses, creating uncertainty for reimbursement decision-makers. We propose a conceptual modelling framework that aligns cost-effectiveness analyses with the biological rationale of precision oncology, evaluating therapies according to shared molecular alterations across tumour types. Patient/material and methods: We examined the methodological limitations of conventional partitioned survival models (PSMs) commonly applied in oncology and evaluated their suitability for tumour-agnostic indications. Based on the collected literature, we developed a dynamic, modular PSM framework that integrates multiple tumour sites expressing a common biomarker. The framework supports pooled and tumour-specific analysis of cost-effectiveness and enables progressive disaggregation of subgroups as additional evidence becomes available.

Results: The proposed modelling approach facilitates transparent synthesis of heterogeneous evidence across tumour types using epidemiologically informed weighting, while preserving the ability to estimate tumour-specific cost-effectiveness where data permit. It addresses key challenges in tumour-agnostic evaluation, including variation in standard of care, treatment effects, and resource use across cancer sites. The modular design promotes internal consistency, reduces duplication of analytical effort, and enables iterative re-assessment of both overall and subgroup-specific cost-effectiveness.

Interpretation: A dynamic, weighted multi-site modelling framework represents a coherent and adaptable extension of current health-technology assessment-practice for tumour-agnostic therapies. By structuring evidence around molecular targets, the framework can improve transparency and robustness of cost-effectiveness estimates, thereby supporting more equitable and efficient reimbursement decisions in the context of precision oncology.

Background and purpose: Distal cholangiocarcinoma (CCA) is a rare malignancy with poor prognosis, even after surgical resection. Accurate staging is essential for guiding treatment and predicting outcomes. The 8th edition of the Union for International Cancer Control (UICC)/The American Joint Committee on Cancer (AJCC) TNM classification introduced depth of tumour invasion (DOI) as the criterion for T-staging (T1-T3) and a three-tiered lymph node (N) classification. This study evaluates patient stratification and prognostic accuracy of the 8th versus 7th edition in a single-centre Western cohort and discusses difficulties with measuring DOI. Patient/material and methods: Patients undergoing pancreatoduodenectomy for distal CCA at Oslo University Hospital (2015-2021) were retrospectively analysed. Tumours were restaged according to the 7th and 8th TNM editions. Survival was assessed using Kaplan-Meier estimates and log-rank tests to compare prognostic accuracy.

Results: Seventy-one patients were included. Using the 7th edition, most cancers (94.4%, 67 patients) were categorised as T3. With the 8th edition, stage redistribution was notable: T2 included 45 patients (63.4%) and T3 included 22 (31.0%). Five-year survival was significantly better for T2 (31.8%) than T3 (10.5%) according to the 8th edition, demonstrating improved discrimination. The revised N classification provided better prognostic distinction, with median survival of 30 months for N1 (1-3 nodes) and 23 months for N2 (≥4 nodes).

Interpretation: The 8th edition provides more accurate prognostic stratification of distal CCA compared to the 7th edition but requires meticulous, standardised pathology assessment to ensure accurate prognosis and appropriate post-surgical management.

Background and purpose: Infections are the leading cause of morbidity and mortality in patients with chronic lymphocytic leukemia (CLL) and occur during and after treatment. When deciding on the type of CLL treatment, the risk of infections is typically assessed based only on age and comorbidities; therefore, there is a need to develop a predictive model that incorporates information from multiple data sources. However, training an effective machine learning model requires a large sample size. Patient/material and methods: In this study, we developed a machine learning approach using domain adaptation (DA) to predict the risk of severe infection during treatment in patients with CLL. We implemented a DA strategy using lymphoma patient data and compared it with a domain-specific (DS) strategy across multiple models.

Results: The DA strategy outperformed the DS strategy across all models, with an odds ratio of 4.43 for infection risk between high-risk and low-risk groups, compared with an odds ratio of 3.69 for the best DS model and 2.27 for the CLL-IPI alone. Explainability analysis identified predictive features for both the DA and DS models, including medication data and biochemistry tests. Specifically, C-reactive protein levels and non-therapeutic drugs were common features identified by both DA and DS models, while the DA models relied more heavily on alimentary tract drugs, solvents and diluting agents, and antibacterial medications.

Interpretation: These findings highlight the value of integrating data from different diseases (lymphoma) to improve predictions in a target disease (CLL), and represent a step toward data-driven identification of CLL patients at high risk of infection during treatment.

Background and purpose: The treatment of advanced non-small cell lung cancer (aNSCLC) with common epidermal growth factor receptor (cEGFR) mutations has evolved substantially over the last 15 years, with the discovery of activating epidermal growth factor receptor (EGFR) mutations and introduction of first-, second- and third generation (gen) EGFR tyrosine kinase inhibitors (TKIs) as first-line therapy. This retrospective observational study aimed to evaluate whether the introduction of these treatments has led to improved 'real-world' outcomes over time by analysing time to next treatment (TTNT) and overall survival (OS). Patient/material and methods: Patients (n = 379) with EGFR exon 19 deletion (Del19) or exon 21 L858R (L858R) substitution and aNSCLC were identified from two Finnish university hospital data lakes between 2010 and 2023. TTNT and OS were analysed from first-line treatment initiation using Kaplan-Meier survival and multivariable Cox regression analyses. Patients were stratified into three cohorts based on date of diagnosis and which TKIs were available at that time (1st-gen: 2010-2016, 2nd-gen: 2017-2020 and 3rd-gen: 2020-2023).

Results: The use of chemotherapy as first-line therapy declined from 32% (2010-2016) to 6% (2020-2023), while 80% of patients received 3rd-gen TKIs as first-line treatment in 2020-2023. Median TTNT improved over time (9.7 to 13.2 to 21.6), with a significant improvement in 2020-2023 versus 2010-2016 (HR: 0.46; 95% CI: 0.33-0.64; p < 0.001). Median OS also increased over time (19.1 to 23.9 to 29.3 months) and was significantly higher in 2020-2023 versus 2010-2016 (HR: 0.56; 95% CI: 0.39-0.82; p = 0.002).

Interpretation: 'Real-world' treatment outcomes for aNSCLC with cEGFR mutations have improved over time likely due to the transition from 1st- to 3rd-gen TKIs. However, real-world survival with TKIs remains lower than clinical trials results emphasizing the unmet need.

Background and purpose: Neoadjuvant therapy (NAT) has become standard therapy for early triple-negative breast cancer (TNBC). The aim of this study was to report real-world outcome of TNBC treated with NAT with or without pembrolizumab and to identify predictive factors for achieving pathologic complete response (pCR) in the pembrolizumab cohort. Patient/material and methods: The data of 75 consecutive TNBC patients treated with neoadjuvant chemotherapy and pembrolizumab at the Helsinki University Hospital Comprehensive Cancer Center were retrospectively collected. Treatment outcome and predictive factors for pCR were analyzed. Additionally, the outcome of nonmatched 102 consecutive TNBC patients treated without pembrolizumab during the preceding years is reported.

Results: Forty-two patients (56.0%) achieved pCR to pembrolizumab-based NAT, while 47 patients (46.1%) without pembrolizumab had pCR. Lymph node metastasis (p = 0.011) and multifocality (p < 0.001) were inversely associated with pCR in the pembrolizumab cohort. Thirty-four patients (45.3%) had immune-related adverse events (irAEs), and 11 patients (14.7%) had grade 1-2 myocarditis in the pembrolizumab cohort. Due to adverse events (AEs), pembrolizumab was discontinued in 22 patients (29.3%) in the neoadjuvant setting, not started postoperatively in 21 patients (28%) and discontinued postoperatively in eight patients (10.7%). The number of preoperative pembrolizumab cycles was not associated with pCR.

Interpretation: Despite higher incidence of myocarditis and interruption of the systemic therapy due to irAEs, higher pCR rates were seen with pembrolizumab. Even though the number of  preoperative pembrolizumab cycles was not associated with pCR monitoring and limiting AEs is important.

Background and purpose: Paediatric low-grade gliomas (pLGG) are the most common brain tumours in children. Radiotherapy, once the standard treatment for unresectable pLGG, is now used less frequently due to concerns about late side effects. The Nordic Society of Paediatric Haematology and Oncology (NOPHO) Radiotherapy Working Group aims to provide consensus guidelines on the use of radiotherapy for pLGG, addressing the current controversies and facilitating decision-making. Patient/material and methods: The guidelines were developed by clinical/radiation oncologists from the Nordic and Baltic countries and two international experts during a 2-day working group meeting. The meeting included presentations from the international experts and was preceded by a survey on radiotherapy practices and a non-systematic review of the literature on pLGG.

Results: We present consensus-based recommendations for radiotherapy of pLGG. The guidelines discuss indications and timing of radiotherapy, age-related considerations, and the impact of genetic predisposition disorders such as neurofibromatosis type 1. Modern radiotherapy techniques, such as proton therapy, are highlighted for their potential to reduce long-term side effects.

Interpretation: Radiotherapy remains the most effective treatment for unresectable pLGG, but its use must be carefully weighed against the risk of long-term side effects. The guidelines emphasise a personalised treatment approach, considering the evolving field of targeted therapies and the importance of multidisciplinary input in decision-making.