Efficacy and safety of antibody-drug conjugates for HR+/HER2-low advanced breast cancer: a systematic review with Bayesian network meta-analysis and real-world study

Introduction

Breast cancer is a major threat to women’s health globally, as it accounted for ~2.3 million cases and 670,000 deaths in just 1 year, 2022 (1). As a key oncogenic driver, human epidermal growth factor receptor 2 (HER2) overexpression has been reported to have a strong correlation with tumor aggressiveness and poor prognosis (2). The introduction of HER2-targeted therapies, such as trastuzumab, has markedly improved survival outcomes in HER2-positive disease (3); however, these benefits are largely restricted to patients with immunohistochemistry (IHC) 3+ or IHC 2+ and fluorescence in situ hybridization (FISH)-positive tumors.

Approximately 40–50% of breast cancers fall within the HER2-low category—defined as IHC 1+ or IHC2+ with FISH negativity—and most of these tumors belong to the hormone receptor-positive (HR+) subtype (2). Traditionally classified as HER2-negative, this population does not benefit from conventional HER2-directed therapies and relies mainly on chemotherapy or endocrine therapy, both of which provide limited and often short-lived efficacy due to the development of resistance (4). Effective strategies against advanced HR+/HER2-low breast cancer, therefore, remain an unachieved therapeutic need.

The emergence of antibody-drug conjugates (ADCs) has introduced new therapeutic opportunities for HER2-low breast cancer (5). The ADCs are reported to enhance the antitumor activity via delivering the cytotoxic agents directly to tumor cells through antibody targeting, besides reducing the toxicity. Moreover, newer ADCs demonstrate a “bystander effect”, assisting cytotoxic effects even against the tumors having low expression levels of HER2. The DESTINY-Breast04 trial first confirmed that trastuzumab deruxtecan (T-DXd) notably prolonged progression-free survival (PFS) and overall survival (OS) in HER2-low advanced breast cancer patients (6), establishing HER2-low disease as a distinct, targetable subtype. Subsequently, the TROPiCS-02 trial showed that sacituzumab govitecan (SG) also provided meaningful clinical benefit in HR+/HER2-low patients (7-9).

However, most recorded evidence is from investigations matching a single ADC with treatment of the physician’s choice (TPC), while direct comparisons amongst the ADCs are lacking (6-10). Conventional meta-analyses, which incorporate only direct evidence, are insufficient for evaluating the relative efficacy and safety across multiple agents. Network meta-analysis (NMA), on the other hand, integrates direct and indirect evidence, enabling comparative assessment of numerous treatments even in the absence of one-on-one trials, and provides higher-level evidence to guide clinical decision-making (11).

We therefore conducted a Bayesian NMA to assess comprehensively the therapeutic potentials and safety of T-DXd, SG, and other ADCs in advanced HR+/HER2-low breast cancer, complemented by real-world data from our institution. Our findings aim to inform drug selection, support individualized treatment strategies, and guide the design of future comparative clinical trials. We present this article in accordance with the PRISMA-NMA reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0043/rc) (12).

Methods

Study design

This study consisted of two components.

The first component was an NMA-based on randomized controlled trials (RCTs) to compare the efficacy and safety of ADCs for HR+/HER2-low advanced breast cancer.

The second component was a single-center real-world study (RWS) conducted to validate the NMA findings and assess treatment effectiveness in routine clinical practice.

The study workflow included:

• Independent analyses of RCT and RWS data;
• Integration of evidence from multiple ADCs through NMA;
• Comparison of the consistency between RCT and RWS results to evaluate potential gaps between trial efficacy and real-world outcomes;
• Joint and sensitivity analyses.

The protocol was preregistered, and no amendments were made. All RWS data were obtained from electronic medical records without direct patient contact; therefore, additional informed consent was not required.

Study population

RCT data sources and eligibility criteria

Globally recognized search engines/databases and tools, primarily PubMed, EMbase, and The Cochrane Library, as well as ASCO, ESMO, and SABCS conference abstracts, with a timeline ranging from inception to December 31, 2025, were used for performing a detailed search. Both subject terms and free-text terms were used, while we manually screened the references used to identify additional records. For trials with multiple publications, the most recent and complete data were used. Search terms included “ADCs”, “trastuzumab deruxtecan”, “sacituzumab govitecan-hziy”, “T-DXd”, “SG”, “breast neoplasms”, and related keywords.

Two independent reviewers appraised the investigation and extracted data, including study characteristics, sample size, interventions, and outcomes. Risk of bias for included RCTs was evaluated using the tool ROB 2.0 (11). The quality assessment plots were then generated.

Inclusion criteria:

• Study design: RCTs published in English or Chinese.
• Participants:
  • Pathologically confirmed advanced breast cancer, including unresectable locally advanced disease, de novo stage IV disease, or recurrent metastatic disease after ≥6 months disease-free survival (DFS) following curative surgery;
  • Confirmed HR [estrogen receptor (ER) and/or progesterone receptor (PR)] positivity by IHC;
    HER2-low expression defined as IHC 1+ or IHC 2+ with FISH negativity (3).
• Interventions: single-agent T-DXd, SG, RC48, SYD985, or MRG002; comparator: TPC.
• Outcomes: at least one reported outcome.
  • Primary: PFS and/or OS;
  • Secondary: objective response rate (ORR), disease control rate (DCR), clinical benefit rate (CBR), grade ≥3 adverse events (AEs) or serious AEs (SAEs).

Exclusion criteria:

• Studies involving combination ADC regimens (e.g., ADC + endocrine therapy) or (neo)adjuvant therapy;
• Studies not limited to HR+/HER2-low advanced breast cancer;
• Incomplete outcome reporting;
• Non-RCTs, systematic reviews, meta-analyses, duplicate publications, case reports, or narrative reviews.

A total of 3 RCTs (7 publications) involving 1,643 patients met the inclusion criteria.

RWS population

This retrospective analysis included HR+/HER2-low advanced breast cancer patients treated with T-DXd or SG at our center between January 2013 and October 2024. HER2-low status was defined according to RCT criteria (3).

Inclusion criteria:

• HER2-low status confirmed by IHC and FISH before ADC treatment, with HR positivity verified by IHC;
• Treatment with an ADC (e.g., T-DXd or SG);
• Patients with recurrent/metastatic disease after prior therapy or those presenting with metastatic disease at initial diagnosis;
• Complete medical records available.

Exclusion criteria:

• Discontinuation of ADCs due to reasons unrelated to treatment efficacy;
• Multiple primary malignancies;
• Participation in clinical trials.

Overall, 22 patients were considered (19 in T-DXd and 3 in SG group).

Outcomes

Primary outcomes were PFS and OS. Secondary outcomes consisted of the ORR, DCR, CBR, and grade ≥3 treatment-related AEs (TRAEs). In the RWS, treatment response was evaluated using RECIST 1.1 criteria (13), and CTCAE v5.0 was used to grade the AEs (10). Follow-up lasted from treatment initiation until disease progression, death, or last contact.

Statistical analysis

Meta-analysis

The Bayesian framework implemented in R (v4.3.2) and STATA (v17.0) was used to conduct NMA:

• Survival outcomes were reported as hazard ratios (HRs) with 95% credible intervals (CIs).
• Dichotomous outcomes were expressed as risk ratios (RRs).

I² and P values were considered for assessing Heterogeneity. A fixed-effects model was applied for I²<50% and P≥0.05; while a random-effects model was used for other cases. The surface under the cumulative ranking curve (SUCRA) was used to rank treatment efficacy and safety. The bias risk was calculated with the help of Cochrane ROB 2.0 tool (11).

Real-world data analysis

PFS and OS were estimated using Kaplan-Meier curves. While median, and intergroup differences were evaluated using the log-rank test. Analyses were performed using SPSSAU software. A two-sided P<0.05 was considered statistically significant. Sensitivity analyses were conducted, including exclusion of small-sample studies and subgroup assessments, to evaluate robustness.

Results

Meta-analysis results

Study selection and basic characteristics

A total of 1,508 records were identified through the initial search. After removing duplicates and studies with unmatched eligibility criteria, three RCTs comprising seven publications were finally included, involving 1,643 patients with HR+/HER2-low advanced breast cancer. The study selection process is shown in Figure 1. The included trials were DESTINY-Breast04 (6,13-16), DESTINY-Breast06 (10,17), and TROPiCS-02 (7-9,18-21). The main study characteristics are summarized in Table 1.

Figure 1 Literature screening flowchart. HER2, human epidermal growth factor receptor 2; HR+, hormone receptor-positive; OS, overall survival; PFS, progression-free survival; RCT, randomized controlled trial.

The trials clearly reported random sequence generation and allocation concealment. Most domains were judged as low risk (green), with a few unclear (yellow), and no high-risk bias was detected. Figure 2 depicts the risk-of-bias plot.

Figure 2 Risk-of-bias assessment of included investigations. Risk of bias summary for the included randomized controlled trials evaluated using the Cochrane Risk of Bias tool. The symbols represent low (green), some concerns (yellow), and high (red) risk of bias across seven domains, assessing the methodological quality of the evidence base.

Feasibility of included data and conventional meta-analysis

All three RCTs reported outcomes including PFS, OS, ORR, DCR, CBR, and grade ≥3 AEs. Overall, ADCs showed significant advantages over TPC across multiple endpoints. PFS demonstrated substantial heterogeneity among studies (I²=85.2%, P=0.001). ADCs significantly enhanced the PFS (HR =0.51, 95% CI: 0.36–0.72) as confirmed by a random-effects model (Figure 3A). OS showed no notable heterogeneity (I²=0.0%, P=0.535); a fixed-effects model indicated a significant OS benefit with ADCs (HR =0.75, 95% CI: 0.65–0.86) (Figure 3B).

Figure 3 Forest plot of outcome measures. Forest plots of conventional pairwise meta-analysis comparing ADCs with TPC. (A) PFS, (B) OS, (C) ORR, (D) DCR, (E) CBR, (F) ≥3 AEs. ADC, antibody-drug conjugate; AEs, adverse events; CBR, clinical benefit rate; CI, credible interval; DCR, disease control rate; DL, dose level; HR, hazard ratio; IV, intravenous; ORR, objective response rate; OS, overall survival; PFS, progression-free survival; TPC, treatment of the physician’s choice.

Compared with TPC, ADCs significantly improved ORR (RR =1.85, 95% CI: 1.30–2.63) and CBR (RR =1.44, 95% CI: 1.16–1.79) (Figure 3C,3D). Although DCR showed a favorable trend, but the difference was insignificant (RR =1.17, 95% CI: 0.98–1.40) (Figure 3E). Regarding safety, the incidence of grade ≥3 AEs was to some extent greater with ADCs compared with TPC (RR =1.21, 95% CI: 1.01–1.46) (Figure 3F).

Sensitivity analyses showed that removing any single study did not materially alter the pooled results, supporting the robustness of the findings (Figure 4).

Figure 4 Sensitivity analysis. Leave-one-out sensitivity analysis for the primary efficacy and safety outcomes. (A) PFS, (B) OS, (C) ORR, (D) DCR, (E) CBR, (F) ≥3 AEs. AEs, adverse events; CBR, clinical benefit rate; CI, credible interval; DCR, disease control rate; ORR, objective response rate; OS, overall survival; PFS, progression-free survival.

Bayesian NMA

The NMA included three RCTs involving three treatment regimens: T-DXd, SG, and TPC. The network geometry is illustrated in Figure 5, where node size is proportional to the number of patients, while line thickness indicates the number of head-to-head comparisons. Direct evidence exists for comparisons of TPC against both T-DXd and SG, while the comparison between T-DXd and SG relies on indirect evidence mediated by TPC.

Figure 5 Network diagram of outcome measures. Network plot showing the evidence structure for treatment comparisons. The size of each node is proportional to the total number of patients randomized to each intervention, while the thickness of the connecting lines represents the number of direct head-to-head comparisons between treatments. (A) PFS, (B) OS, (C) ORR, (D) DCR, (E) CBR, (F) ≥3 AEs. AEs, adverse events; CBR, clinical benefit rate; DCR, disease control rate; ORR, objective response rate; OS, overall survival; PFS, progression-free survival; T-DXd, trastuzumab deruxtecan; TPC, treatment of the physician’s choice.

Regarding efficacy outcomes, SUCRA analysis indicated that T-DXd had the highest exploratory probability of being ranked first for PFS (0.791) and all tumor response indicators, while SG showed a higher probability of benefit for OS (0.728). Specifically, T-DXd induced higher PFS compared to TPC (HR =0.48; 95% CI: 0.20–1.17), whereas SG showed a numerical advantage in OS over both TPC (HR =1.35; 95% CI: 0.83–2.18, favorable to SG) and T-DXd (HR =1.03; 95% CI: 0.57–1.84), though neither survival endpoint reached statistical significance among the groups. However, given that these estimates are based on a network of only three RCTs, these SUCRA values should be interpreted as hypothesis-generating rather than definitive clinical rankings. In terms of tumor response, T-DXd showed a numerical trend toward being the top-ranked intervention (SUCRA: ORR 0.819; DCR 0.803; CBR 0.833) and demonstrated statistically significant improvements compared to TPC in both DCR (RR =0.32; 95% CI: 0.11–0.88) and CBR (RR =3.60; 95% CI: 1.06–12.60); while T-DXd also numerically outperformed SG in ORR, DCR, and CBR, these pairwise differences were not statistically significant (Figure 6 and Table 2).

Figure 6 Probability ranking charts for each outcome indicator for different scenarios. (A) PFS, (B) OS, (C) ORR, (D) DCR, (E) CBR, (F) ≥3 AEs. Y-axis represents the rank probability. The three colored bars represent the three compared regimens: T-DXd, SG, and TPC. AEs, adverse events; CBR, clinical benefit rate; DCR, disease control rate; ORR, objective response rate; OS, overall survival; PFS, progression-free survival; SG, sacituzumab govitecan; T-DXd, trastuzumab deruxtecan; TPC, treatment of the physician’s choice.

Relative treatment effects (league table analysis)

The league table results further substantiate the findings described above. For survival outcomes, T-DXd maintained favorable HR values in both direct and indirect comparisons versus SG and TPC. Most notably, T-DXd showed the most substantial improvement in PFS against TPC (Table 3), whereas SG demonstrated a slight, non-significant numerical advantage over T-DXd in OS. Overall, T-DXd showed a favorable trend in delaying disease progression, while SG held a marginal advantage in long-term survival, though the evidence remains inconclusive.

Regarding tumor response (ORR, DCR, and CBR), T-DXd consistently demonstrated numerical advantages across comparisons. Specifically, T-DXd achieved statistically significant improvements against TPC in DCR (RR =0.32; 95% CI: 0.11–0.88) and CBR (RR =3.60; 95% CI: 1.06–12.60) (Tables 4,5). With regards to safety, T-DXd exhibited lowest occurrence of grade ≥ AEs, whereas SG showed a relatively higher rate, although pairwise differences did not reach statistical significance. Synthesizing the league table and SUCRA rankings, T-DXd suggested a potential advantage across multiple efficacy endpoints while maintaining a manageable safety profile. These findings indicate that T-DXd may be a promising therapeutic consideration in the third-line setting, although the lack of head-to-head evidence and the limited number of included trials necessitate caution in prioritizing one ADC over another.

RWS results

Baseline characteristics

In all, 991 patients were diagnosed with advanced breast cancer at the authors’ institute between January 2013 and October 2024, 286 (27.8%) of whom were classified as HER2-low. Within this HER2-low cohort, 232 patients (81.1%) were HER2 IHC 1+, and 44 (15.3%) were IHC 2+/FISH-negative or untested. A total of 44 patients (15.3%) received ADC therapy. Out of them, 22 patients (50%) were confirmed as HR+/HER2-low and were thus considered. From these 19 received T-DXd, while 3 received SG. On December 15, 2024, the median follow-up duration was 9 months. Four deaths occurred, and no patients were lost to follow-up (Table 6). Notably, this real-world cohort is limited by its small sample size and potential baseline imbalances, as patients were not randomized or matched by propensity scores.

The age range of the included patients was 38–71 years. All patients were heavily pretreated, having received ≥3 lines of systemic therapy before ADC initiation, including chemotherapy, endocrine therapy, and targeted therapy. The majority had prior exposure to CDK4/6 inhibitors. The brain and liver were the most common sites of metastasis.

Survival outcomes

At the data cutoff, the overall median PFS (mPFS) was 4 months (95% CI: 2.00–6.00) for patients with HR+/HER2-low advanced breast cancer treated with ADCs (Figure 7A). Subgroup analysis revealed that the mPFS in the T-DXd group was 5 months (95% CI: 2.50–9.00), against 2 months (95% CI: 1.00–2.00) observed in SG group (Figure 7B,7C). This difference was significant based on the log-rank test (²=7.143, P=0.008). Median OS (mOS) data for T-DXd and SG were not yet mature due to the relatively short follow-up period.

Figure 7 Kaplan-Meier survival curves. The Kaplan-Meier survival curve of the RWS cohort. (A) PFS of the overall population; (B) OS of the overall population; (C) comparative analysis of clinical practice data between T-DXd group and SG group. OS, overall survival; PFS, progression-free survival; RWS, real-world study; SG, sacituzumab govitecan; T-DXd, trastuzumab deruxtecan.

Discussion

This study systematically evaluated the potency and safety of T-DXd, SG, and TPC based on data from three RCTs involving 1,643 patients with HR+/HER2-low advanced breast cancer. Results indicate that ADCs significantly prolonged PFS (HR =0.51) and OS (HR =0.75) compared to TPC, while also achieving statistical advantages in ORR and CBR, confirming the survival benefit of ADCs in this population. The SUCRA rankings from the Bayesian NMA placed T-DXd first for PFS improvement, whereas SG was slightly superior for OS improvement. This suggests that the efficacy difference between the two agents is marginal and may be attributable to individual patient heterogeneity and treatment sequencing. In this NMA, T-DXd showed a numerically higher SUCRA value in the efficacy outcome, while SG showed a better ranking in some safety outcomes. However, these rankings are based on indirect comparisons and should not be interpreted as evidence of efficacy superiority in the absence of head-to-head trials. However, due to the limited number of included trials and the lack of head-to-head comparison, the SUCRA results should be regarded as the basis for “generating hypotheses” rather than “changing clinical practice”. The SUCRA value in this study reflects the exploratory probability of becoming the best treatment plan in the included treatment plan.

The included studies (DESTINY-Breast04, DESTINY-Breast06, and TROPiCS-02) focused on endocrine-refractory populations (6,7,10). In DESTINY-Breast04, T-DXd significantly extended PFS (10.1 vs. 5.4 months) and OS (23.9 vs. 17.5 months) (6). These findings support recommendations from the European Society for Medical Oncology (ESMO) 2023 consensus and the 2024 Chinese Society of Clinical Oncology (CSCO) guidelines, that suggest prioritizing T-DXd after prior treatment with CDK4/6 inhibitors and at least a line of chemotherapy (22,23).

Similarly, SG demonstrated an OS benefit (HR =0.79) in the TROPiCS-02 trial, although the difference was not statistically significant (24). Collectively, T-DXd demonstrated the most pronounced survival extension in the HR+/HER2-low population, a finding consistent with the results of the present study.

Regarding tumor response, the ADC group significantly improved ORR (RR =1.85) and CBR (RR =1.44), with T-DXd showing superior response rates compared to SG. This aligns with the meta-analysis reported by Dacoregio et al. (25). These results suggest that ADC therapy can achieve deeper tumor remission and improve patient symptoms and quality of life, providing a new standard option for later-line treatment.

Corresponding to the safety concerns, an overall incidence of grade ≥ AEs in the ADC group was slightly greater than the TPC group. Among the regimens, SG had the highest incidence of grade ≥ AEs, while T-DXd had the lowest. Common adverse reactions for T-DXd included neutropenia, anemia, and fatigue, with an interstitial lung disease (ILD) incidence of approximately 12% (mostly grade 1–2) (26). SG-related AEs were primarily neutropenia and diarrhea, with no reported ILD (10,24). This discrepancy may be related to differences in ADC targets (HER2 vs. TROP2) and drug tissue distribution. Clinical practice requires strengthened monitoring and early intervention for ILD to reduce the risk of severe AEs.

Beyond T-DXd and SG, various novel ADCs (e.g., RC48, SYD985, MRG002) have shown potential in HER2-low breast cancer (27-31). Notably, RC48 achieved an ORR of 33.3% and a PFS of 5.1 months in phase I studies (28), suggesting that the HER2-low population may benefit from a broader range of ADC agents. However, these studies are mostly early-phase trials lacking large-scale phase III evidence and require further validation.

The real-world analysis in this study included 22 HR+/HER2-low advanced breast cancer patients. Results showed that the mPFS in the T-DXd was superior to SG group (5 and 2 months, respectively), consistent with trends observed in clinical trials. Owing to the limited sample size and later lines of therapy, OS data remained immature. Actual efficacy is influenced by multiple factors, including treatment timing, drug accessibility, insurance policies, and confounding from combination therapies, warranting validation through future multi-center prospective studies.

Mechanistically, these types of cancer may possess diverse molecular features. Patients with HER2-low or ultra-low expression can still benefit from the “bystander effect” of ADCs, wherein the drug releases its cytotoxic payload to affect neighboring tumor cells with lower HER2 expression (32). This mechanism provides a theoretical basis for the application of ADCs across broader breast cancer subtypes.

Future research directions include three aspects: (I) exploration of combination therapies: SG or T-DXd combined with immunotherapy (e.g., MORPHEUS-panBC and SACI-IO studies) has shown trends toward improved PFS and ORR (33) and warrants further evaluation; (II) early-stage application: investigating the efficacy and translational potential of ADCs in early-stage HR+/HER2-low patients; and (III) optimization of detection: standardization of HER2 testing and multi-point sampling strategies could improve detection rates in low-expression cases, providing a basis for precision treatment.

Despite systematically integrating existing RCTs and real-world data, this study has its own limits. First, the number of included RCTs is limited (n=3), and the overall sample size is relatively small, with some data derived from conference abstracts or preliminary results, resulting in a restricted level of evidence. Second, the lack of direct head-to-head trials comparing ADCs introduces heterogeneity, necessitating reliance on random-effects models for some analyses. Third, the inability to conduct subgroup analysis based on individual patient data (IPD) prevented adequate control for potential confounding factors such as prior treatment lines and metastatic sites. Furthermore, as the real-world component of this investigation restricted to a relatively small sample size, single-center retrospective design, and short follow-up duration, which in turn might have led to selection bias and confounding, it thus might limit the universality of the findings. Finally, the real-world component of this study has several important limitations. The RWS cohort is characterized by a relatively small and imbalanced sample size. Due to the characteristics of the real-world data of the center, propensity score matching method cannot be implemented, resulting in imbalances in factors such as previous treatment options and physical fitness at the baseline level. Therefore, the RWS results should be viewed as supplementary evidence intended to support the RCT findings and provide a hypothetical basis for future large-scale prospective studies, rather than as confirmatory evidence for comparative effects. Future research should validate efficacy differences among ADCs in various HER2 subtypes through multi-center, prospective, large-scale studies. Concurrently, incorporating personalized biomarkers (e.g., dynamic TROP2 or HER2 expression levels) to optimize patient stratification, alongside unified testing standards and efficacy assessment systems, will enhance the reliability and clinical guidance value of study results.

Conclusions

Synthesizing the findings of this study, both T-DXd and SG exhibited substantial therapeutic advantages over TPC in the treatment of HR+/HER2-low advanced breast cancer. Compared to traditional chemotherapy regimens, ADC therapy significantly prolonged PFS and OS, improved ORR and CBR, and maintained a generally manageable safety profile. Considering factors such as comprehensive efficacy and AE incidence, T-DXd exhibited a superior overall profile in this population, positioning it as a preferred therapeutic option, while SG serves as a viable alternative for subsequent lines of therapy.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA-NMA reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0043/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0043/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0043/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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