Rare Special Breast Cancer Histologies in the ALTTO Trial: Central Histology Review and Outcomes

Rare Special Breast Cancer Histologies in the ALTTO Trial: Central Histology Review and Outcomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Rare Special Breast Cancer Histologies in the ALTTO Trial: Central Histology Review and Outcomes Riccardo Gerosa, Guilherme Nader-Marta, Lieveke Ameye, Giuseppe Viale, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9082124/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Rare special histological subtypes (rST) account for ~10% of early-stage breast cancer (eBC) but their prognostic value remains poorly defined, particularly in HER2-positive disease. This sub-analysis of patients with HER2-positive eBC treated with adjuvant trastuzumab-based therapy in the ALTTO trial (NCT00490139) aims to compare baseline characteristics and clinical outcomes between patients with rST (n=239) and those with invasive carcinoma of no special type (NST, n=5,981). Among the cases with central histopathological review (n=5,302), 82% of locally diagnosed rST cases were reclassified as NST. When adjusted for baseline differences between different rST and NST, the histological subtype was not associated with survival outcomes. Non-significant trends of better outcomes were observed for mucinous subgroup (n=35) (10-year OS: 96.6% vs 88.2%, aHR 0.41, 95%CI 0.06–2.93). Although rST did not have independent prognostic value in HER2-positive eBC setting, the high diagnostic discordance raises concerns about existing evidence supporting differential management according to rST. Biological sciences/Cancer Health sciences/Oncology Early breast cancer HER2-positive Central Pathology Review Mucinous carcinoma Apocrine carcinoma Micropapillary carcinoma Cribriform carcinoma Metaplastic carcinoma Mixed NST-ILC Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Breast cancer (BC) is the most diagnosed cancer in women worldwide 1 , 2 . Nearly 90% of BC cases are diagnosed at an early stage (eBC), where multimodal therapy offers the potential for cure 3 . BC is a highly heterogeneous disease, with 21 distinct histological subtypes recognized by the World Health Organization (WHO) 4 , 5 . Invasive carcinoma of no special type (NST), accounts for approximately 75% of all BC and its pathological diagnosis is defined by the absence of specific histological features 6 . Conversely, the remaining 25% of BC cases are classified as special types (ST) based on distinct cellular morphology, growth patterns, and architecture. It has been shown that each one of them has also distinct clinicopathological and diagnostic features, treatment responses, recurrence patterns, and long-term outcomes, likely driven by a distinct yet largely unexplored genomic landscape 7 – 9 . Invasive lobular carcinoma (ILC) is the most common subtype, representing half of ST cases 10 . The remaining histological entities, despite individually rare or ultra-rare (rST), collectively account for nearly 10% of all BC cases in total. This, combined with the overall high incidence of BC, translates into a substantial number of rST cases expected each year, making them far from uncommon in daily clinical practice. However, evidence on rST remain almost exclusively derived from heterogeneous and at times contradictory retrospective studies, small case series and case reports 11 – 13 . Moreover, interpretation of available data could be further challenged by variability in pathological assessments conducted across different institutions, time periods and evolving WHO classification criteria 14 . Interestingly, within luminal-like and triple-negative subtypes, certain rST have demonstrated either favorable clinical behavior or lack of benefit from adjuvant standard options, prompting consideration of treatment de-escalation in selected cases 3 , 15 . For example, both the National Comprehensive Cancer Network (NCCN) and European Society of Medical Oncology (ESMO) guidelines acknowledge that adjuvant chemotherapy may be omitted in low-risk triple-negative adenoid cystic carcinoma, secretory carcinoma, and certain low-grade metaplastic subtypes. Likewise, the NCCN guideline states that ET can be withheld in pure, low-grade, localized luminal-like tubular, Cribriform and Mucinous. On the other hand, while some data suggest that, when evaluated together, human epidermal growth factor receptor 2-positive (HER2-positive) rST could have better outcomes compared to HER2-positive NST 11 , they continue to be managed exactly as the latter according to international guidelines. Moreover, although limited, heterogeneous, and sometimes inconsistent evidence, some studies suggest that individual HER2-positive rST may have indeed a different prognosis and response to anti-HER2 treatments 11 , 16 – 26 . Furthermore, considering that certain rare entities display frequent HER2 positivity, as in Apocrine and Micropapillary carcinomas, where it can reach up to 50% of cases, further evidence in this context is therefore urgently needed 27 , 28 . To address this evidence gap, we conducted a sub-analysis of the phase III randomized “Adjuvant Lapatinib and/or Trastuzumab Treatment Optimisation (ALTTO)” trial (NCT00490139) 29 – 31 . Beyond being a valuable source of prospective data on HER2-positive eBC cases treated with trastuzumab (T)-based adjuvant therapy, it provided high-quality and reliable data on rST, since histological diagnoses were confirmed through central pathology review. Thus, we identified rST patients enrolled in the trial and analyzed them individually, focusing on clinicopathological features, treatment patterns, and long-term outcomes. RESULTS Out of all patients diagnosed with HER2-positive eBC and treated with T-based regimen in the ALTTO trial (N = 6,281), 5,302 patients (84.4%) had an available revision, resulting in 5,981 (96.2%) with NST and 239 (3.8%) with rST after exclusion of 61 cases of pure ILC (Fig. 1 ). Among 322 patients initially diagnosed with rST, only 45 (14%) were confirmed, while 7 were recognized as a different rST. In contrast, the vast majority (n = 267) were reclassified as NST, and 4 as pure ILC (as shown in Fig. 2 and fully detailed in Table S1 ). Notably, the highest diagnostic concordance within rST was observed for Mucinous, Metaplastic, and Micropapillary subtypes (Fig. 3 ). On the other hand, nearly all of locally assessed NST were corroborated (97.5%), while the few remaining cases were reclassified as: Apocrine (n = 64), Micropapillary (n = 20), ILC (n = 11), mixed NST‑ILC (n = 10), Metaplastic (n = 8), Mucinous (n = 6) and Cribriform (n = 1). Baseline clinicopathological features Among the 239 patients with rST, of which nearly one-third (n = 71) originated from cohorts centrally reviewed elsewhere (USA and China), the subtypes included were Apocrine (1.2%, n = 77), mixed NST‑ILC (0.9%, n = 58), Micropapillary (0.6%, n = 36), Mucinous (0.6%, n = 35), Cribriform (0.3%, n = 22), and Metaplastic (0.2%, n = 11) (Table 1 ). Several baseline clinicopathological characteristics differed significantly across histology, taking NST as reference. For instance, all rST patients were female, while male cases (n = 7) were reported only within NST group. Some geographical and race differences were as well observed. Nearly all Cribriform cases, more frequently diagnosed in Black patients (18.2% vs 1.4%, p < 0.001), were enrolled from North America (95.5% vs 10.5%, p < 0.001), a geographical pattern also observed for mixed NST–ILC (51.7% vs 10.5%, p < 0.001). Mucinous cases were less often reported from Europe (28.6% vs 53.7%, p = 0.004) ( Table S2 ). Moreover, Mucinous subtype was characterized by a higher proportion of well or moderately differentiated tumors (64.7% vs 39.3%, p = 0.003) and more frequent use of adjuvant ET (81.8% vs 57.5%, p = 0.003), consistent with a numerically greater prevalence of estrogen and/or progesterone receptor-positive (ER-positive) disease (71.4% vs 59.4%, p = 0.09). Mixed NST–ILC similarly showed more ER-positive tumors (84.5% vs 57.4%, p < 0.001), leading to greater ET use (p < 0.001), but also received anthracycline-free adjuvant chemotherapy regimen more often (25.9% vs 4.8%, p < 0.001) and concomitantly with anti-HER2 therapy (74.1% vs 44.5%, p < 0.001). Cribriform cases, likewise, were less often treated with anthracyclines (50% vs 4.8%, p < 0.001) but instead received more frequently carboplatin-containing regimens concomitant with anti-HER2 therapy (100% vs 44.5%, p < 0.001). Patients in the Cribriform subgroup were also more commonly randomized to treatment arms containing lapatinib (95.5% vs 65.5%, p < 0.001) and tended numerically to present with smaller tumors (≤ 2 cm: 72.7% vs 45.3%, p = 0.009). By contrast, Micropapillary was distinguished only by greater nodal involvement (72.2% vs 51.2%, p = 0.001), while Apocrine showed a markedly higher rate of ER-negative tumors (92.2% vs 42.6%, p < 0.001), translating into less frequent ET (p < 0.001) and, despite otherwise similar features to NST, a higher use of adjuvant RT (84.4% vs 71.2%, p = 0.007) (Table 1 and Table S2 ). Table 1 Clinicopathological Comparison of rST and NST. Summary of major clinicopathological features by histological subtype, with significant differences (in at least one rST compared to NST, taken as the reference) highlighted in bold, based on pairwise comparisons. Statistical significance was set at P < 0.008 (0.05/6) (Bonferroni method) to take into account multiple testing. Absolute numbers are shown, with percentages in parentheses calculated relative to the number of cases within each histological subtype. Histological grade , n (%) NST n = 5981 (96.2%) APOCRINE n = 77 (1.2%) MIXED NST-ILC n = 58 (0.9%) MICROPAPILLARY n = 36 (0.6%) MUCINOUS n = 35 (0.6%) CRIBRIFORM n = 22 (0.4%) METAPLASTIC n = 11 (0.2%) Poorly or undifferentiated or cannot be assessed 3617 (60.7%) 56 (72.7%) 34 (58.6%) 19 (52.8%) 12 (35.3%) 10 (45.5%) 9 (81.8%) Well or moderately differentiated 2340 (39.3%) 21 (27.3%) 24 (41.4%) 17 (47.2%) 22 (64.7%) 12 (54.5%) 2 (18.2%) Missing 24 0 0 0 1 0 0 P.value (NST vs rST) Reference 0.03 0.75 0.34 0.003 0.15 0.22 Hormone-receptor status , n (%) ER and PgR negative 2548 (42.6%) 71 (92.2%) 9 (15.5%) 10 (27.8%) 10 (28.6%) 5 (22.7%) 8 (72.7%) ER and/or PgR positive 3433 (57.4%) 6 (7.8%) 49 (84.5%) 26 (72.2%) 25 (71.4%) 17 (77.3%) 3 (27.3%) P.value (NST vs rST) Reference < 0.001 < 0.001 0.07 0.09 0.05 0.06 Lymph node involvement (N class) , n (%) Not applicable (neoadjuvant chemotherapy) 508 (8.5%) 9 (11.7%) 0 (0.0%) 0 (0.0%) 1 (2.9%) 0 (0.0%) 0 (0.0%) 0 2411 (40.3%) 24 (31.2%) 25 (43.1%) 10 (27.8%) 18 (51.4%) 8 (36.4%) 6 (54.5%) 1 1744 (29.2%) 23 (29.9%) 17 (29.3%) 9 (25.0%) 13 (37.1%) 10 (45.5%) 5 (45.5%) 2 1318 (22.0%) 21 (27.3%) 16 (27.6%) 17 (47.2%) 3 (8.6%) 4 (18.2%) 0 (0.0%) P.value (NST vs rST) Reference 0.33 0.01 0.001 0.07 0.31 0.49 Adjuvant Chemotherapy type n (%) Not available 3319 (55.5%) 36 (46.8%) 15 (25.9%) 14 (38.9%) 19 (54.3%) 0 (0.0%) 8 (72.7%) Taxane only 2373 (39.7%) 40 (51.9%) 28 (48.3%) 21 (58.3%) 12 (34.3%) 11 (50.0%) 3 (27.3%) Taxane + Carboplatin 289 (4.8%) 1 (1.3%) 15 (25.9%) 1 (2.8%) 4 (11.4%) 11 (50.0%) 0 (0.0%) P.value (NST vs rST) Reference 0.04 < 0.001 0.08 0.28 < 0.001 0.64 Adjuvant ET type , n (%) No ET 2541 (42.5%) 60 (77.9%) 10 (17.2%) 15 (41.7%) 12 (34.3%) 4 (18.2%) 8 (72.7%) SERM only 1274 (21.3%) 4 (5.2%) 14 (24.1%) 6 (16.7%) 16 (45.7%) 8 (36.4%) 1 (9.1%) AI only 1072 (17.9%) 5 (6.5%) 15 (25.9%) 11 (30.6%) 6 (17.1%) 4 (18.2%) 1 (9.1%) SERM + AI only 458 (7.7%) 3 (3.9%) 7 (12.1%) 2 (5.6%) 0 (0.0%) 1 (4.5%) 0 (0.0%) LHRH/oophorectomy 636 (10.6%) 5 (6.5%) 12 (20.7%) 2 (5.6%) 1 (2.9%) 5 (22.7%) 1 (9.1%) P.value (NST vs rST) Reference < 0.001 < 0.001 0.37 0.003 0.05 0.53 Legend : Absolute number (n), percentage (%), rare special histological subtype (rST), Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular breast carcinoma (Mixed NST-ILC), Estrogen Receptor (ER), Progesterone Receptor (PgR), Endocrine therapy (ET), Selective Estrogen Receptor Modulator (SERM), Aromatase Inhibitor (AI), Luteinizing Hormone-Releasing Hormone analogue (LHRH), centimetres (cm). Outcomes According to Histology After a median follow-up of 9.8 years (interquartile range 6.9–10.0), no statistically significant differences in disease-free survival (DFS) were observed between NST (reference) and any rST subgroup (Fig. 4 ), even after adjustment for major clinicopathological variables ( Table S3 ). Similarly, overall survival (OS) showed no significant variation across histologies (Fig. 5 , Table 2 ). Time to central nervous system (CNS) ( Figure S1 ) and distant relapse (TTDR) ( Figure S2 ) equally did not display any meaningful differences. Only numerically better outcomes were observed for Mucinous compared to NST, consistently in terms of DFS (10-years DFS: 89.1% vs 78.1%; adjusted Hazard Ratio [aHR] 0.52, 95% confidential interval [CI] 0.17–1.62), OS (10-years OS: 96.6% vs 88.2%; aHR 0.41, 95% CI 0.06–2.93), TTDR (HR 0.51, 95% CI 0.13–1.96) and time to CNS relapse (HR 0.67, 95% CI 0.09–4.66). Considering all rST together, both CNS (1.67% vs. 2.14%) and extracranial distant relapse rates (5.8% vs. 9.0%) were numerically lower in comparison with NST ( Table S4 ). However, when metastatic spread occurred, rSTs showed a numerical greater tendency for visceral involvement (55.5% vs. 44.3%, p = 0.35), while fewer soft tissue (5.5% vs. 11.7%, p = 0.71) and bone recurrences (16.6% vs. 24.8%, p = 0.58) were recorded. Lastly, only Apocrine had a numerically worse time to CNS recurrence (HR 1.48; 95% CI, 0.61–3.62), although this was not statistically significant. Table 2 OS multivariate analysis. Multivariate Cox regression model was used to assess the independent association of each histological subtypes with OS; HR with corresponding 95% CI and p-values from Wald tests are reported to assess the strength and statistical significance of each association. Events/Total HR (95% CI) P-value 1 617/6169 Histology NST 599/5933 Reference Mixed NST-ILC 3/58 0.69 (0.22–2.16) 0.5218 Apocrine 8/76 0.96 (0.48–1.94) 0.9070 Micropapillary 3/36 0.84 (0.27–2.64) 0.7709 Cribriform 1/22 1.13 (0.16–8.14) 0.9030 Mucinous 1/33 0.41 (0.06–2.93) 0.3744 Metaplastic 2/11 1.99 (0.49–8.02) 0.3341 Menopausal status at baseline Postmenopausal or male 391/3466 Reference Premenopausal 226/2703 0.71 (0.59–0.84) 0.0001 Tumor Size (T class) ≤ 2 cm 192/2794 Reference > 2 cm 425/3375 1.67 (1.40–1.98) < .0001 Lymph node involvement (N class) 0 125/2487 Reference 1 135/1804 1.51 (1.18–1.93) 0.0009 2 252/1364 3.54 (2.84–4.40) < .0001 Not applicable (Neoadjuvant chemotherapy) 105/514 4.44 (3.41–5.79) < .0001 Histological Grade Well or moderately differentiated 218/2428 Reference Poorly differentiated, undifferentiated or cannot be assessed 399/3741 1.12 (0.95–1.33) 0.1761 Hormone receptor status ER and/or PgR positive 318/3535 Reference ER and PgR negative 299/2634 0.83 (0.64–1.08) 0.1621 Adjuvant Chemotherapy type Not available 380/3379 Reference Taxane only 214/2470 0.80 (0.68–0.95) 0.0119 Taxane + Carboplatin 23/320 0.84 (0.55–1.29) 0.4348 Adjuvant ET type No ET 308/2621 Reference SERM only 122/1317 0.79 (0.58–1.07) 0.1301 AI only 112/1108 0.66 (0.49–0.91) 0.0098 SERM + AI only 22/467 0.32 (0.20–0.52) < .0001 LHRH/oophorectomy 53/656 0.61 (0.43–0.86) 0.0052 Trial planned treatment Trastuzumab alone 229/2064 Reference Trastuzumab concomitant with Lapatinib 194/2058 0.87 (0.71–1.05) 0.1398 Trastuzumab followed by Lapatinib 194/2047 0.88 (0.72–1.06) 0.1765 1 Covariate Wald p-value; Legend : overall survival (OS); hazard ratio (HR); 95% confidence interval (95% CI), Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular breast carcinoma (Mixed NST-ILC), Estrogen Receptor (ER), Progesterone Receptor (PgR), Endocrine therapy (ET), Selective Estrogen Receptor Modulator (SERM), Aromatase Inhibitor (AI), Luteinizing Hormone-Releasing Hormone analogue (LHRH). DISCUSSION In this retrospective secondary analysis of the large phase III ALTTO trial, we evaluated rST within a large HER2-positive eBC cohort, using centrally reviewed pathology and long-term clinical follow-up. Each rST entity showed distinct baseline clinicopathological profiles compared with NST, although treatment patterns were largely similar. Despite these differences, long-term outcomes were comparable across histologies, with nearly 90% of patients alive at 10 years and no significant differences in DFS or OS between each rST and NST. Substantial discordance was observed in the histological diagnosis assessment for rSTs: upon central review at a high-volume center with dedicated breast pathology expertise, approximately 80% of cases locally diagnosed as rST were reclassified as NST, whereas fewer than 3% of locally diagnosed NST cases were reassigned to a rare subtype. Previous studies have consistently reported substantial discrepancies between centralized and local assessments, particularly for tumor grade, extent of residual disease, and HER2 and ER expression 32 – 35 . In contrast, only a limited number of studies have specifically examined inter-observer concordance for histological diagnosis, reporting at best moderate agreement 36 , 37 . A particularly informative observation comes from the MINDACT trial (NCT00433589), a multicenter phase III study including nearly 7,000 eBC patients, predominantly of luminal-like subtype, in which central pathology review was similarly performed at a reference laboratory 38 . Only approximately 30% of tumors locally classified as “other” rare histologies were indeed confirmed upon central review, with a similar pattern observed for ILC, while about 10% of locally diagnosed NST were reclassified as rST 39 . Consistent with these findings, our results in the HER2-positive scenario further highlight the limited reliability of rST diagnosis in routine local practice and support the need for confirmation at high-volume centers with dedicated breast pathology expertise. This is particularly relevant for subtypes considered prognostically “exceptionally” favorable, where misclassification could lead to inappropriate treatment de-escalation. Moreover, as the already limited body of evidence on rST largely derives from retrospective studies without central histological confirmation, our results call into question the robustness and reliability of existing data overall. Therefore, if this observation is further validated in other large independent cohorts, it prompts a reconsideration of current pathological diagnostic protocols, including cross-laboratory validation and dedicated training for pathologists. In this regard, digital pathology integrated with artificial intelligence holds promise to substantially improve diagnostic accuracy, reproducibility, and consistency 40 . In line with previous reported evidence, another key finding of this study is that HER2-positive rSTs exhibit distinct clinicopathological features compared with both their HER2-negative counterparts and HER2-positive NST 11 , 12 , 41 . However, whether analyzed unadjusted or after accounting for these subtype-specific baseline differences, we did not observe a significantly different prognosis for each rSTs in this setting compared to NST. This finding contrasts with prior reports in which HER2-positive rSTs, when analysed collectively, were described as having more favourable outcomes than HER2-positive NST 11 . Similarly, when individual histological subtypes are examined separately, HER2-positive mucinous tumours have been reported to have more favourable outcomes, despite some inconsistencies and presenting with more aggressive features and exhibiting worse prognosis compared with their HER2-negative counterparts 11 , 21 , 23 , 24 , 42 . In our cohort, mucinous tumours likewise showed higher 10-year OS (96.6% vs 88.2%) and DFS (89.1% vs 78.1%) compared with NST. In contrast, HER2-positive micropapillary carcinomas have been associated with poorer outcomes than HER2-positive NST 20 , 41 , whereas apocrine, metaplastic, and mixed NST–ILC subtypes, consistent with our findings, have previously been described as having survival comparable outcomes 17 – 19 , 41 , 43 . Notably, no subtype-specific data have previously been reported for cribriform carcinomas in the HER2-positive setting, likely reflecting the rarity of HER2 positivity in this subtype, yet in our cohort, it also demonstrated outcomes comparable to HER2-positive NST 16 . However, interpretation of these concordant or discordant findings with prior literature remains challenging due to substantial inter-study heterogeneity and methodological limitations, including differing reference groups, limited multivariable adjustment, small sample sizes, variable grouping of distinct histological sub-entities, and temporal or institutional differences in pathological criteria and cut-off definitions for ‘pure’ rSTs. Consequently, definitive conclusions regarding the prognostic significance of individual HER2-positive rSTs and their implications for possible tailored treatment strategies, distinct from NST, cannot yet be drawn. Along this line, our findings underscore the urgent need for large, dedicated ideally prospective studies using standardized and reliable histological classifications to better uncover this uncertainty. Moreover, in the context of the rapidly evolving peri-operative treatment landscape for HER2-positive eBC, elucidating subtype-specific sensitivity or resistance to novel therapies is equally critical to move beyond the current one-size-fits-all approach 44 , 45 . Future registrational trials on this trajectory should acknowledge the heterogeneity of rSTs by collecting with dedicated effort subtype-specific data rather than grouping these tumors with NST or within a generic “other” category. Moreover, while a limited number of genomic signatures currently guide treatment decisions in selected NSTs and others are under development specifically in the HER2-positive setting (e.g., HER2DX), their applicability to rSTs remains unknown 38 , 46 , 47 . Validating such tools in this context and deeper investigation of their largely unexplored genomic landscape of rSTs, likely responsible for their distinct presentation and behaviour, may enable a shift toward more robust prognostic and predictive stratification beyond histology alone 9 , 48 , 49 , Our analysis has several strengths. This study leverages high-quality data from a large phase III trial and represents, to our knowledge, the largest cohort of patients with HER2-positive rST eBC with prospectively collected information. As such, it provides unprecedented insights into a largely unexplored setting, including entities for which evidence had previously been generated (e.g., cribriform carcinoma). The robustness of our findings is further supported by the extended follow-up, with 10-year outcomes reported not only for OS and DFS, but also for TTDR and CNS relapse. A major additional strength lies in the central confirmation of histological diagnoses making this, again to our knowledge, also the largest eBC cohort with centralized histopathological review, a critical aspect given the observed risk of diagnostic discordance. Moreover, while the minor differences between WHO classification editions were incorporated into our analysis, the successive updates of the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) HER2 testing guidelines over the years are unlikely to have had a meaningful impact on our findings. On the other hand, one limitation of the study is that central pathological reassessment was performed on a single tumor block per patient. For heterogeneous tumors, this could have led to misclassification if the selected block were not fully representative by reflecting the morphological diversity. Moreover, despite central pathological review being available for most patients (> 5,000), approximately one third of the rST cases included were derived from patients without central review. Consequently, some degree of misclassification cannot be excluded, and the true prevalence of rSTs may therefore be lower than reported. To account for this issue, we performed a sensitivity analysis restricted to centrally reviewed cases. Within this subset, analyses were limited to the apocrine subgroup, as it was the only subgroup with ≥ 10 survival events, allowing for meaningful comparison. Results were consistent with the primary analysis, showing no significant differences versus NST for either DFS (HR 1.00; 95% CI 0.601–1.665; p = 1.00) or OS (HR 1.14; 95% CI 0.59–2.20; p = 0.69). Indeed, despite the relatively large rST cohort, the very low number of events in the rarest subtypes (< 5 in some cases) overall limited statistical power. As such, definitive conclusions should be taken with caution, and a reliable assessment of the potential added benefit of specific adjuvant therapies (e.g., aromatase inhibitors versus tamoxifen) within individual subtypes remains unfeasible. Lastly, given that anti-HER2 peri-operative treatment strategies have evolved substantially over the past decade, the study population may not fully reflect current clinical practice. Nonetheless, patients treated with earlier-generation regimens achieved excellent long-term outcomes, suggesting that many would not have required the newer, more intensive therapies reserved for higher-risk disease. METHODS ALTTO (NCT00490139) was a large-scale international phase III trial that prospectively evaluated escalation of adjuvant trastuzumab-based therapy with the addition of lapatinib, an anti-HER2 tyrosine kinase inhibitor, in HER2-positive eBC. Between June 2007 and July 2011, 8,381 patients were recruited through nearly one thousand centres spanning 44 countries across four continents, using a randomized, open-label design. Briefly, the main aim was to evaluate escalation of adjuvant trastuzumab-based therapy through the addition of lapatinib. The detailed trial design, eligibility criteria, patient characteristics, and main results have been previously described 29 , 31 , 50 . As the lapatinib-alone arm was found to be inferior, it was prematurely closed in 2011 following a protocol amendment, and the 2,.100 patients enrolled in that arm were excluded from the analysis. Histological Central Review and Regrouping of Study Population Figure 1 graphically illustrates the methodological workflow, outlining the step-by-step process of regrouping and reclassification from initial local histological diagnoses to final categorization. Given the substantial heterogeneity of local histological reports, originating from more than 900 centers across nearly 50 countries, a preliminary harmonization of the original pathology data was first performed under the supervision of an expert BC pathologist (GV). Subsequently, information from the central pathological review was incorporated. This review was conducted across the three dedicated central laboratories, all high-volume institutions with recognized expertise in breast pathology: the European Institute of Oncology (IEO) in Milan, Italy, for most international participants; the Mayo Clinic (Rochester, Minnesota, and Scottsdale, Arizona) for North American patients; and the Peking Union Medical College Hospital for Chinese patients. Each central laboratory received a single representative tumor block per patient and performed a full reassessment, either confirming or reclassifying the local diagnosis, evaluating histological subtype, tumor grade, and HER2/estrogen/progesterone receptor status according to the WHO Breast Tumors Classification (3rd edition) and scoring criteria in use at the time of enrollment. Although central review was carried out for all regions, central histotype data from the U.S. and Chinese cohorts were not included in the dataset available for this analysis; therefore, local pathology reports were used for these cases. To enable robust statistical evaluation and align results with contemporary diagnostic standards, regrouping of all cases into the final analytical categories was then performed by the expert pathologist (GV) on the basis of predefined assumptions (detailed in Fig. 1 ) and the latest WHO Breast Tumors Classification (5th edition). Finally, pure ILC cases were excluded, as it represents the second most common histological subtype of BC overall and the most frequent ST, and therefore does not fall within the definition of rare entities. Objectives and statistical analysis The randomization process, statistical methodology, and endpoints of ALTTO trial have been previously reported 29 , 31 , 50 . The present sub analysis was aimed to explore the baseline clinico-pathological features and long-term outcomes of rST compared to NST (used as reference), in patients with HER2-positive eBC receiving a T-based adjuvant regimen. Patients and tumor baseline features were analysed using descriptive statistics. Differences in continuous variables were assessed with the Wilcoxon or t-test; differences in categorical variables were assessed with the chi-square test or Fisher Exact test. As six rare histologies (apocrine, mixed NST-ILC, micropapillary, mucinous, cribriform and metastatic) were compared to NST, we considered the Bonferroni method for multiple testing, i.e. a P-value < 0.05/6 which is < 0.008 as statistically significant. DFS was measured from the date of randomization to the earliest of the following events, including invasive recurrence of BC, diagnosis of a new primary malignancy (contralateral BC or non-breast cancer), or death from any cause. Overall survival corresponded to the time elapsed from randomization until death, irrespective of cause. TTDR was defined as the interval from randomization to the first occurrence of either distant metastatic recurrence or death from any cause, whichever occurred first. Time to CNS recurrence was defined as the interval from randomization to the first documented occurrence of CNS metastasis or death from any cause, whichever occurred first. Survival functions were estimated using the Kaplan‑Meier method. Adjusted HR with 95% CI and covariate‑Wald p‑values were calculated using a multivariate Cox regression model, adjusting for menopausal status at baseline, tumor size, lymph node involvement, grade, adjuvant chemo, adjuvant endocrine therapy and the randomization arm. TTDR and time to CNS recurrence were analyzed using cumulative incidence functions. Due to the very small number of events/cases in the rare histology groups (DFS, OS, CNS and TTDR), the survival analyses are exploratory and the statistical power to detect any difference is very low. Declarations Author contributions Riccardo Gerosa and Guilherme Nader-Marta contributed to the conceptualization, data curation, writing of the original draft, and to review and editing. Ameye Lieveke contributed to data curation and formal analysis and to writing, review and editing. Giuseppe Viale contributed to conceptualization, data curation, and to writing, review and editing. All other authors (Diogo Martins-Branco, Marianne Paesmans, Philippe Aftimos, Armando Santoro, Anup Choudhury, Marco Colleoni, Martine Piccart-Gebhart, Evandro de-Azambuja) contributed to the writing of the manuscript, review and editing. Acknowledgements We thank each and every one of the patients who participated in the Adjuvant Lapatinib and/or Trastuzumab Treatment Optimisation (ALTTO) study; the Breast European Adjuvant Study Team (BrEAST) Data Center; the Frontier Science (FS) team; the Breast International Group (BIG) headquarters; the US National Cancer Institute (NCI); the North Central Cancer Treatment Group (NCCTG; now part of the Alliance for Clinical Trial in Oncology); the ALTTO Executive and Steering Committee members; the Independent Data Monitoring Committee (IDMC) members; the Cardiac Advisory Board members; the three central pathology laboratories; GlaxoSmithKline; Novartis; physicians, nurses, trial coordinators and pathologists. We thank from BIG: Celine Schurmans, Orsolya Birta, Amal Arahmani, Theodora Goulioti, Panayota Boussis; from BrEAST: Daniela D. Rosa, Kamal Saini, Otto Metzger Filho, Sébastien Guillaume, Sylvia Napoleone and Christophe Lecocq; from FS: Robin McConnell, Vicki Paterson, Christine Campbell, Eleanor McFadden, Emma Paterson, Faye Samy and Garrick Kassab for their scientific, statistics and/or project management support. Data availability The data that support the findings of this study are available from 19 th November 2024, but restrictions apply to the availability of these data, which were used under licence for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of BIG and Institute Jules Bordet. Code availability Not applicable Funding statement This research received no specific grant number from any funding agency in the public, commercial, or not-for-profit sectors. Human Ethics and Consent to Participate declarations Not applicable to the present exploratory study. All patients provided written informed consent to participate in the ALTTO trial. Institutional review board or ethics committee approval was obtained and was mandatory for all participating centers. The study was conducted in accordance with ethical standards and the Declaration of Helsinki. Competing Interests: R. Gerosa: meeting/travel support grants: Novartis, Daiichii Sankyo, Lilly, Menarini G. Nader Marta: Meeting/travel grants to attend medical conference: AstraZeneca D. Martins-Branco reports employment with the European Society for Medical Oncology (ESMO) since September 1, 2023; participation as medical research fellow in research studies institutionally funded by Eli Lilly, F Hoffmann-La Roche Ltd and Novartis to Institute Jules Bordet (2021-2023); and non-financial interests as past member of the Board of Directors for the Associação de Investigação e Cuidados de Suporte em Oncologia (2022-2024) and member of the American Society of Clinical Oncology, Associação Portuguesa de Cuidados Paliativos, Multinational Association of Supportive Care in Cancer and Sociedade Portuguesa de Oncologia PAftimos: Consulting: Boehringer Ingelheim, Macrogenics, Roche, Novartis, Amcure, Servier, G1 Therapeutics, Radius, Deloitte, Daiichi Sankyo, Olema. Honoraria: Synthon, Amgen, Novartis, Gilead, Lilly, Menarini. Travel grants: Amgen, MSD, Pfizer, Roche, Daiichi Sankyo. Research funding to my institution: Roche A Santoro: consulting or advisory roles for Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp & Dohme, Sanofi, and Incyte; and participation in speakers bureaus for Takeda, Roche, AbbVie, Amgen, Celgene, AstraZeneca, Lilly, Sandoz, Novartis, Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp & Dohme, and ArQule G. Viale: Financial Interests, Personal, Advisory Board: Roche, AstraZeneca, Daiichi Sankyo, MSD Oncology, Pfizer; Financial Interests, Personal, Other, Consulting fees: Agilent; Financial Interests, Personal, Invited Speaker: Gilead; Financial Interests, Personal, Other, Educational webinar: Medscape; Financial Interests, Institutional, Invited Speaker: AstraZeneca; Financial Interests, Institutional, Research Grant: Roche. M. Lambertini: advisory role for Roche, Lilly, Novartis, AstraZeneca, Pfizer, Seagen, Gilead, MSD, Pierre Fabre, Menarini, Exact Sciences, Nordic Pharma; speaker honoraria from Roche, Lilly, Novartis, Pfizer, Sandoz, Libbs, Daiichi Sankyo, Takeda, Ipsen, Menarini and AstraZeneca; travel grants from Gilead, Roche, and Daiichi Sankyo; research funding (to his institution) from Gilead; nonfinancial interests as a member of the national council of the Italian Association of Medical Oncology (AIOM) A. Choudhury: Financial Interests, Personal, Other, Working as a full time Clinical Development Medical Director and company stocks provided as per compensation plan: Novartis Healthcare Pvt. Ltd M.A. Colleoni: Non-Financial Interests, Personal, Other, Co-Chair Scientific Committee: International Breast Cancer Study Group M. Piccart: Board Member Scientific Board: Oncolytics. Consultant (honoraria): AstraZeneca, Gilead, Lilly, Menarini, Mersana, MSD, Novartis, Pfizer, Roche-Genentech, Seattle Genetics, Seagen, NBE Therapeutics, Summit Therapeutics Research grants to my Institute : AstraZeneca, Lilly, Menarini, MSD, Novartis, Pfizer, Roche-Genentech, Servier, Gilead E. de Azambuja: Financial Interests, Personal, Advisory Board: Roche/GNE, Novartis,SeaGen, MSD; Financial Interests, Personal, Invited Speaker: Zodiac, Libbs, Pierre Fabre, Lilly, AstraZeneca, Gilead Sciences; Financial Interests, Personal, Other, Chair of the Gilead Sciences Research Scholars Program in Solid Tumours: Gilead Sciences; Financial Interests, Personal, Other, Roche WO43571 IDMC: Roche/Genentech; Financial Interests, Institutional, Research Grant: Roche/GNE, AstraZeneca, GSK/Novartis, Servier; Financial Interests, Institutional, Other, Travel Grant: Roche/GNE; Financial Interests, Institutional, Invited Speaker: MSD, ABCSG, Nektar, Gilead, Immunomedics, Synthon, Odonate Therapeutics; Financial Interests, , Invited Speaker, ASCENT 04: Gilead; Financial Interests, , Invited Speaker, Aphinity, Lorelei, Impassion03: Roche; Financial Interests, , Invited Speaker, AURORA: Breast International Group; Financial Interests, , Invited Speaker, Olympia: AstraZeneca; Financial Interests, Personal, Other, Travel grant: AstraZeneca; Financial Interests, Personal, Other, Travel Grant SABCS 2024: Gilead; Financial Interests, Institutional, Other, Scholarship grant for 2025-2026 for Luca Arecco: Gilead Sciences; Financial Interests, Institutional, Invited Speaker, Research grant for the TUCANIBE retrospective study: Pfizer; Non-Financial Interests, , Advisory Role, Member of the cardio-oncology council: European Society of Cardiology (ESC), Belgian Society of Cardiology; Non- Financial Interests, , Advisory Role, Belgium governmental institution for cancer: KCE; Non-Financial Interests, , Other, Editorial board member: ESMO Open; Non-Financial Interests, , Advisory Role: Anticancer Fund; Non-Financial Interests, Leadership Role, President 2023-2026: Belgian Society of Medical Oncology (BSMO) All other authors declare not conflict of interest related to the manuscript References Siegel, R. 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Nader Marta: Meeting/travel grants to attend medical conference: AstraZeneca • D. Martins-Branco reports employment with the European Society for Medical Oncology (ESMO) since September 1, 2023; participation as medical research fellow in research studies institutionally funded by Eli Lilly, F Hoffmann-La Roche Ltd and Novartis to Institute Jules Bordet (2021-2023); and non-financial interests as past member of the Board of Directors for the Associação de Investigação e Cuidados de Suporte em Oncologia (2022-2024) and member of the American Society of Clinical Oncology, Associação Portuguesa de Cuidados Paliativos, Multinational Association of Supportive Care in Cancer and Sociedade Portuguesa de Oncologia • PAftimos: Consulting: Boehringer Ingelheim, Macrogenics, Roche, Novartis, Amcure, Servier, G1 Therapeutics, Radius, Deloitte, Daiichi Sankyo, Olema. Honoraria: Synthon, Amgen, Novartis, Gilead, Lilly, Menarini. Travel grants: Amgen, MSD, Pfizer, Roche, Daiichi Sankyo. Research funding to my institution: Roche • A Santoro: consulting or advisory roles for Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp & Dohme, Sanofi, and Incyte; and participation in speakers bureaus for Takeda, Roche, AbbVie, Amgen, Celgene, AstraZeneca, Lilly, Sandoz, Novartis, Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp & Dohme, and ArQule • G. Viale: Financial Interests, Personal, Advisory Board: Roche, AstraZeneca, Daiichi Sankyo, MSD Oncology, Pfizer; Financial Interests, Personal, Other, Consulting fees: Agilent; Financial Interests, Personal, Invited Speaker: Gilead; Financial Interests, Personal, Other, Educational webinar: Medscape; Financial Interests, Institutional, Invited Speaker: AstraZeneca; Financial Interests, Institutional, Research Grant: Roche. • M. Lambertini: advisory role for Roche, Lilly, Novartis, AstraZeneca, Pfizer, Seagen, Gilead, MSD, Pierre Fabre, Menarini, Exact Sciences, Nordic Pharma; speaker honoraria from Roche, Lilly, Novartis, Pfizer, Sandoz, Libbs, Daiichi Sankyo, Takeda, Ipsen, Menarini and AstraZeneca; travel grants from Gilead, Roche, and Daiichi Sankyo; research funding (to his institution) from Gilead; nonfinancial interests as a member of the national council of the Italian Association of Medical Oncology (AIOM) • A. Choudhury: Financial Interests, Personal, Other, Working as a full time Clinical Development Medical Director and company stocks provided as per compensation plan: Novartis Healthcare Pvt. Ltd • M.A. Colleoni: Non-Financial Interests, Personal, Other, Co-Chair Scientific Committee: International Breast Cancer Study Group • M. Piccart: Board Member Scientific Board: Oncolytics. Consultant (honoraria): AstraZeneca, Gilead, Lilly, Menarini, Mersana, MSD, Novartis, Pfizer, Roche-Genentech, Seattle Genetics, Seagen, NBE Therapeutics, Summit Therapeutics Research grants to my Institute : AstraZeneca, Lilly, Menarini, MSD, Novartis, Pfizer, Roche-Genentech, Servier, Gilead • E. de Azambuja: Financial Interests, Personal, Advisory Board: Roche/GNE, Novartis,SeaGen, MSD; Financial Interests, Personal, Invited Speaker: Zodiac, Libbs, Pierre Fabre, Lilly, AstraZeneca, Gilead Sciences; Financial Interests, Personal, Other, Chair of the Gilead Sciences Research Scholars Program in Solid Tumours: Gilead Sciences; Financial Interests, Personal, Other, Roche WO43571 IDMC: Roche/Genentech; Financial Interests, Institutional, Research Grant: Roche/GNE, AstraZeneca, GSK/Novartis, Servier; Financial Interests, Institutional, Other, Travel Grant: Roche/GNE; Financial Interests, Institutional, Invited Speaker: MSD, ABCSG, Nektar, Gilead, Immunomedics, Synthon, Odonate Therapeutics; Financial Interests, , Invited Speaker, ASCENT 04: Gilead; Financial Interests, , Invited Speaker, Aphinity, Lorelei, Impassion03: Roche; Financial Interests, , Invited Speaker, AURORA: Breast International Group; Financial Interests, , Invited Speaker, Olympia: AstraZeneca; Financial Interests, Personal, Other, Travel grant: AstraZeneca; Financial Interests, Personal, Other, Travel Grant SABCS 2024: Gilead; Financial Interests, Institutional, Other, Scholarship grant for 2025-2026 for Luca Arecco: Gilead Sciences; Financial Interests, Institutional, Invited Speaker, Research grant for the TUCANIBE retrospective study: Pfizer; Non-Financial Interests, , Advisory Role, Member of the cardio-oncology council: European Society of Cardiology (ESC), Belgian Society of Cardiology; Non- Financial Interests, , Advisory Role, Belgium governmental institution for cancer: KCE; Non-Financial Interests, , Other, Editorial board member: ESMO Open; Non-Financial Interests, , Advisory Role: Anticancer Fund; Non-Financial Interests, Leadership Role, President 2023-2026: Belgian Society of Medical Oncology (BSMO) • All other authors declare not conflict of interest related to the manuscript Supplementary Files ALTTOrarehistologiesSupplementary10032026.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 03 May, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviewers invited by journal 31 Mar, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 24 Mar, 2026 First submitted to journal 10 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9082124","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":615290622,"identity":"aeafff12-802a-4bea-a50b-0344a92bf6f4","order_by":0,"name":"Riccardo Gerosa","email":"data:image/png;base64,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","orcid":"","institution":"Hôpital Universitaire de Bruxelles (H.U.B), Université Libre de Bruxelles (ULB)","correspondingAuthor":true,"prefix":"","firstName":"Riccardo","middleName":"","lastName":"Gerosa","suffix":""},{"id":615290623,"identity":"2601ba31-8f9b-4259-a36d-4b1e9a034576","order_by":1,"name":"Guilherme Nader-Marta","email":"","orcid":"","institution":"Hôpital Universitaire de Bruxelles (H.U.B), Université Libre de Bruxelles (ULB)","correspondingAuthor":false,"prefix":"","firstName":"Guilherme","middleName":"","lastName":"Nader-Marta","suffix":""},{"id":615290624,"identity":"f680ebf0-3f22-4335-921a-4662b5c3f31f","order_by":2,"name":"Lieveke Ameye","email":"","orcid":"","institution":"Université Libre de Bruxelles","correspondingAuthor":false,"prefix":"","firstName":"Lieveke","middleName":"","lastName":"Ameye","suffix":""},{"id":615290626,"identity":"bf4f2b53-55c6-47dc-9409-840b4efdc0df","order_by":3,"name":"Giuseppe Viale","email":"","orcid":"","institution":"IEO - 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Istituto Europeo di Oncologia IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"","lastName":"Colleoni","suffix":""},{"id":615290652,"identity":"1407182b-f918-4911-acf5-f8a81e3a8d98","order_by":10,"name":"Martine Piccart-Gebhart","email":"","orcid":"","institution":"Hôpital Universitaire de Bruxelles (H.U.B), Université Libre de Bruxelles (ULB)","correspondingAuthor":false,"prefix":"","firstName":"Martine","middleName":"","lastName":"Piccart-Gebhart","suffix":""},{"id":615290655,"identity":"ce583fd0-2731-4f74-ad06-85c25a856313","order_by":11,"name":"Evandro de Azambuja","email":"","orcid":"","institution":"Hôpital Universitaire de Bruxelles (H.U.B), Université Libre de Bruxelles (ULB)","correspondingAuthor":false,"prefix":"","firstName":"Evandro","middleName":"","lastName":"de Azambuja","suffix":""}],"badges":[],"createdAt":"2026-03-10 09:38:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9082124/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9082124/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106189362,"identity":"6a3b4aa9-7da8-4789-8d03-c83032aa3ec0","added_by":"auto","created_at":"2026-04-05 17:09:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":267084,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWorkflow for deriving final histological categories\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlowchart summarizing the stepwise process leading to the final histological classification of the study population. From top to bottom, the diagram illustrates: (i) initial local histological reports, (ii) expert-guided (GV) regrouping of cases, (iii) central pathology review according to the WHO 3rd edition, and (iv) final reclassification** based on specific assumptions and the latest WHO 5th edition. White boxes report the number of cases for each histological entity at every stage, while light-blue boxes indicate the main review steps. In the last row, the ILC box is crossed out to indicate its exclusion from the final evaluated cohort. Figure created with Microsoft PowerPoint on 26th September 2025.\u003c/p\u003e\n\u003cp\u003e* Various Histological entities, including:\u003c/p\u003e\n\u003cp\u003e· Tumors with a main histological type (e.g., NST, ILC, etc.) that exhibit features such as: “intraductal/comedo type/comedonic/comedo/comedocarcinoma”, “trabeculae/trabecular solid”, “pleomorphic”, “intracyst papillar/papillary”, “papilliferous”, “scrirrhous”, “squamoid features”, “signet-ring cell”, “sarcomatoid”, “metaplastic carcinoma”, “metaplastic carcinoma with cartilaginous/osseus metaplasia”.\u003c/p\u003e\n\u003cp\u003e· Tumors locally classified as: “papillary invasive carcinoma”, “adenosquamous carcinoma”, “invasive mucoepidermoid”, “spheroidal cell carcinoma”, “squamous cell carcinoma”.\u003c/p\u003e\n\u003cp\u003e** The regrouping approach considered:\u003c/p\u003e\n\u003cp\u003e· Medullary carcinoma has been reclassified under NST, according to the WHO 5th edition.\u003c/p\u003e\n\u003cp\u003e· Cribriform and tubular carcinomas have been merged into the “cribriform” subtype, supposed that the cribriform component was prevalent and \u0026gt;90% (as per the WHO 5th edition classification new required cut-off).\u003c/p\u003e\n\u003cp\u003e· Apocrine carcinoma has been retained as such, rather than being reclassified as “carcinoma with apocrine differentiation”.\u003c/p\u003e\n\u003cp\u003e· Mixed tumours (coming from the cohort without available central review data) combining special types and NST (such as Micropapillary-NST, Cribriform-NST) have been reclassified assuming that special type component was above \u0026gt;90% cut-off.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eLegend\u003c/u\u003e: Breast cancer (BC), Not Otherwise Specified (NOS); World Health Organization (WHO), Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular carcinoma (Mixed NST-ILC), European Institute of Oncology (IEO), United States of America (USA).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9082124/v1/da7744ccede8fdd469ce41b2.jpg"},{"id":106402933,"identity":"4c9eed3c-5cb5-4e3a-ae56-cf2c0e196f0d","added_by":"auto","created_at":"2026-04-08 09:13:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43251,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHistological reclassification upon central pathological review\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach panel presents a Sankey diagram of histological subtype reclassification after central pathology review. Flows show the transition from the initial local diagnosis (left) to the central review diagnosis (right), with the corresponding number of cases indicated. Panels (a), (b), and (c) illustrate the reclassification of rST (blue node), ILC (red node), and NST (green node), respectively. When cases were reclassified as rST or into another rST subgroup, the flow to the final specific subtype is shown for clarity. Figure generated with SankeyArt.com, accessed on 26th September 2025.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eLegend\u003c/u\u003e: Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular carcinoma (Mixed NST-ILC).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9082124/v1/de111882235a2499136c1cfd.jpg"},{"id":106189368,"identity":"e6c2e407-21d9-45aa-b0ce-1ad3b292ea7b","added_by":"auto","created_at":"2026-04-05 17:09:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":90212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConcordance of histological diagnosis among rST.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe bar chart compares, for each rST subtype, the number of cases identified by local pathological assessment (left, light blue) with the number subsequently confirmed by central review (right, green). Concordance rates are reported below each subtype. Figure created with Microsoft Excel on 26th September 2025. \u003cu\u003eLegend:\u003c/u\u003e Mixed ductal and lobular carcinoma (Mixed NST-ILC).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9082124/v1/83245d804d8b210eb453d7d9.jpg"},{"id":106189364,"identity":"8693955f-f3a5-4367-9cbe-3b0930dda22d","added_by":"auto","created_at":"2026-04-05 17:09:51","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":92033,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDFS by Histological Subtype.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach Kaplan–Meier curve refers to a different histological subtype, as indicated in the colour legend below, with the corresponding number of events for DFS, HR (95% CI), and KM est at 5- and 10-year time points. L\u003cu\u003eegend\u003c/u\u003e: Hazard Ratio (HR), 95% Confidence Interval (95% CI), Kaplan–Meier estimate (KM est), Disease-free survival (DFS), Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular breast carcinoma (Mixed NST-ILC),\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9082124/v1/7ee80da80de3ad8bd824e6a7.jpg"},{"id":106189479,"identity":"4dfba914-9a38-460c-b366-a61ad8faca49","added_by":"auto","created_at":"2026-04-05 17:10:00","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":91316,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOS by Histological Subtype.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach Kaplan–Meier curve refers to a different histological subtype, as indicated in the colour legend below, with the corresponding number of events for OS, HR (95% CI), and KM est at 5- and 10-year time points. Figure created with GraphPad on 26th September 2025. \u003cu\u003eLegend\u003c/u\u003e: Hazard Ratio (HR), 95% Confidence Interval (95% CI), Kaplan–Meier estimate (KM est), Overall survival (OS), Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular breast carcinoma (Mixed NST-ILC).\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9082124/v1/ab1614a2163111a7c4bb66d6.jpg"},{"id":106405679,"identity":"7113719a-5099-496c-8423-c5fc1e5d45e2","added_by":"auto","created_at":"2026-04-08 09:28:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1987459,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9082124/v1/ffab3c9c-7771-425d-91cf-5057bc2c435d.pdf"},{"id":106189473,"identity":"43fe70ce-ab62-4902-895c-b8f0b4e351ed","added_by":"auto","created_at":"2026-04-05 17:10:00","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":809785,"visible":true,"origin":"","legend":"","description":"","filename":"ALTTOrarehistologiesSupplementary10032026.docx","url":"https://assets-eu.researchsquare.com/files/rs-9082124/v1/e42082654ca674f1ce2ca453.docx"}],"financialInterests":"Competing interest reported. •\tR. Gerosa: meeting/travel support grants: Novartis, Daiichii Sankyo, Lilly, Menarini (all outside the current work) \n•\tG. Nader Marta: Meeting/travel grants to attend medical conference: AstraZeneca \n•\tD. Martins-Branco reports employment with the European Society for Medical Oncology (ESMO) since September 1, 2023; participation as medical research fellow in research studies institutionally funded by Eli Lilly, F Hoffmann-La Roche Ltd and Novartis to Institute Jules Bordet (2021-2023); and non-financial interests as past member of the Board of Directors for the Associação de Investigação e Cuidados de Suporte em Oncologia (2022-2024) and member of the American Society of Clinical Oncology, Associação Portuguesa de Cuidados Paliativos, Multinational Association of Supportive Care in Cancer and Sociedade Portuguesa de Oncologia\n•\tPAftimos: Consulting: Boehringer Ingelheim, Macrogenics, Roche, Novartis, Amcure, Servier, G1 Therapeutics, Radius, Deloitte, Daiichi Sankyo, Olema. Honoraria: Synthon, Amgen, Novartis, Gilead, Lilly, Menarini. Travel grants: Amgen, MSD, Pfizer, Roche, Daiichi Sankyo. Research funding to my institution: Roche\n•\tA Santoro: consulting or advisory roles for Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp \u0026 Dohme, Sanofi, and Incyte; and participation in speakers bureaus for Takeda, Roche, AbbVie, Amgen, Celgene, AstraZeneca, Lilly, Sandoz, Novartis, Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp \u0026 Dohme, and ArQule\n•\tG. Viale: Financial Interests, Personal, Advisory Board: Roche, AstraZeneca, Daiichi Sankyo, MSD Oncology, Pfizer; Financial Interests, Personal, Other, Consulting fees: Agilent; Financial Interests, Personal, Invited Speaker: Gilead; Financial Interests, Personal, Other, Educational webinar: Medscape; Financial Interests, Institutional, Invited Speaker: AstraZeneca; Financial Interests, Institutional, Research Grant: Roche.\n•\tM. Lambertini: advisory role for Roche, Lilly, Novartis, AstraZeneca, Pfizer, Seagen, Gilead, MSD, Pierre Fabre, Menarini, Exact Sciences, Nordic Pharma; speaker honoraria from Roche, Lilly, Novartis, Pfizer, Sandoz, Libbs, Daiichi Sankyo, Takeda, Ipsen, Menarini and AstraZeneca; travel grants from Gilead, Roche, and Daiichi Sankyo; research funding (to his institution) from Gilead; nonfinancial interests as a member of the national council of the Italian Association of Medical Oncology (AIOM)\n•\tA. Choudhury: Financial Interests, Personal, Other, Working as a full time Clinical Development Medical Director and company stocks provided as per compensation plan: Novartis Healthcare Pvt. Ltd\n•\tM.A. Colleoni: Non-Financial Interests, Personal, Other, Co-Chair Scientific Committee: International Breast Cancer Study Group\n•\tM. Piccart: Board Member Scientific Board: Oncolytics. Consultant (honoraria): AstraZeneca, Gilead, Lilly, Menarini, Mersana, MSD, Novartis, Pfizer, Roche-Genentech, Seattle Genetics, Seagen, NBE Therapeutics, Summit Therapeutics Research grants to my Institute : AstraZeneca, Lilly, Menarini, MSD, Novartis, Pfizer, Roche-Genentech, Servier, Gilead \n•\tE. de Azambuja: Financial Interests, Personal, Advisory Board: Roche/GNE, Novartis,SeaGen, MSD; Financial Interests, Personal, Invited Speaker: Zodiac, Libbs, Pierre Fabre, Lilly, AstraZeneca, Gilead Sciences; Financial Interests, Personal, Other, Chair of the Gilead Sciences Research Scholars Program in Solid Tumours: Gilead Sciences; Financial Interests, Personal, Other, Roche WO43571 IDMC: Roche/Genentech; Financial Interests, Institutional, Research Grant: Roche/GNE, AstraZeneca, GSK/Novartis, Servier; Financial Interests, Institutional, Other, Travel Grant: Roche/GNE; Financial Interests, Institutional, Invited Speaker: MSD, ABCSG, Nektar, Gilead, Immunomedics, Synthon, Odonate Therapeutics; Financial Interests, , Invited Speaker, ASCENT 04: Gilead; Financial Interests, , Invited Speaker, Aphinity, Lorelei, Impassion03: Roche; Financial Interests, , Invited Speaker, AURORA: Breast International Group; Financial Interests, , Invited Speaker, Olympia: AstraZeneca; Financial Interests, Personal, Other, Travel grant: AstraZeneca; Financial Interests, Personal, Other, Travel Grant SABCS 2024: Gilead; Financial Interests, Institutional, Other, Scholarship grant for 2025-2026 for Luca Arecco: Gilead Sciences; Financial Interests, Institutional, Invited Speaker, Research grant for the TUCANIBE retrospective study: Pfizer; Non-Financial Interests, , Advisory Role, Member of the cardio-oncology council: European Society of Cardiology (ESC), Belgian Society of Cardiology; Non- Financial Interests, , Advisory Role, Belgium governmental institution for cancer: KCE; Non-Financial Interests, , Other, Editorial board member: ESMO Open; Non-Financial Interests, , Advisory Role: Anticancer Fund; Non-Financial Interests, Leadership Role, President 2023-2026: Belgian Society of Medical Oncology (BSMO)\n•\tAll other authors declare not conflict of interest related to the manuscript","formattedTitle":"Rare Special Breast Cancer Histologies in the ALTTO Trial: Central Histology Review and Outcomes","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer (BC) is the most diagnosed cancer in women worldwide \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Nearly 90% of BC cases are diagnosed at an early stage (eBC), where multimodal therapy offers the potential for cure \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. BC is a highly heterogeneous disease, with 21 distinct histological subtypes recognized by the World Health Organization (WHO) \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Invasive carcinoma of no special type (NST), accounts for approximately 75% of all BC and its pathological diagnosis is defined by the absence of specific histological features \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Conversely, the remaining 25% of BC cases are classified as special types (ST) based on distinct cellular morphology, growth patterns, and architecture. It has been shown that each one of them has also distinct clinicopathological and diagnostic features, treatment responses, recurrence patterns, and long-term outcomes, likely driven by a distinct yet largely unexplored genomic landscape \u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Invasive lobular carcinoma (ILC) is the most common subtype, representing half of ST cases \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The remaining histological entities, despite individually rare or ultra-rare (rST), collectively account for nearly 10% of all BC cases in total. This, combined with the overall high incidence of BC, translates into a substantial number of rST cases expected each year, making them far from uncommon in daily clinical practice. However, evidence on rST remain almost exclusively derived from heterogeneous and at times contradictory retrospective studies, small case series and case reports \u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Moreover, interpretation of available data could be further challenged by variability in pathological assessments conducted across different institutions, time periods and evolving WHO classification criteria \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInterestingly, within luminal-like and triple-negative subtypes, certain rST have demonstrated either favorable clinical behavior or lack of benefit from adjuvant standard options, prompting consideration of treatment de-escalation in selected cases \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. For example, both the National Comprehensive Cancer Network (NCCN) and European Society of Medical Oncology (ESMO) guidelines acknowledge that adjuvant chemotherapy may be omitted in low-risk triple-negative adenoid cystic carcinoma, secretory carcinoma, and certain low-grade metaplastic subtypes. Likewise, the NCCN guideline states that ET can be withheld in pure, low-grade, localized luminal-like tubular, Cribriform and Mucinous. On the other hand, while some data suggest that, when evaluated together, human epidermal growth factor receptor 2-positive (HER2-positive) rST could have better outcomes compared to HER2-positive NST \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, they continue to be managed exactly as the latter according to international guidelines. Moreover, although limited, heterogeneous, and sometimes inconsistent evidence, some studies suggest that individual HER2-positive rST may have indeed a different prognosis and response to anti-HER2 treatments \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Furthermore, considering that certain rare entities display frequent HER2 positivity, as in Apocrine and Micropapillary carcinomas, where it can reach up to 50% of cases, further evidence in this context is therefore urgently needed \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo address this evidence gap, we conducted a sub-analysis of the phase III randomized \u0026ldquo;Adjuvant Lapatinib and/or Trastuzumab Treatment Optimisation (ALTTO)\u0026rdquo; trial (NCT00490139) \u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Beyond being a valuable source of prospective data on HER2-positive eBC cases treated with trastuzumab (T)-based adjuvant therapy, it provided high-quality and reliable data on rST, since histological diagnoses were confirmed through central pathology review. Thus, we identified rST patients enrolled in the trial and analyzed them individually, focusing on clinicopathological features, treatment patterns, and long-term outcomes.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOut of all patients diagnosed with HER2-positive eBC and treated with T-based regimen in the ALTTO trial (N\u0026thinsp;=\u0026thinsp;6,281), 5,302 patients (84.4%) had an available revision, resulting in 5,981 (96.2%) with NST and 239 (3.8%) with rST after exclusion of 61 cases of pure ILC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among 322 patients initially diagnosed with rST, only 45 (14%) were confirmed, while 7 were recognized as a different rST. In contrast, the vast majority (n\u0026thinsp;=\u0026thinsp;267) were reclassified as NST, and 4 as pure ILC (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and fully detailed in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Notably, the highest diagnostic concordance within rST was observed for Mucinous, Metaplastic, and Micropapillary subtypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). On the other hand, nearly all of locally assessed NST were corroborated (97.5%), while the few remaining cases were reclassified as: Apocrine (n\u0026thinsp;=\u0026thinsp;64), Micropapillary (n\u0026thinsp;=\u0026thinsp;20), ILC (n\u0026thinsp;=\u0026thinsp;11), mixed NST‑ILC (n\u0026thinsp;=\u0026thinsp;10), Metaplastic (n\u0026thinsp;=\u0026thinsp;8), Mucinous (n\u0026thinsp;=\u0026thinsp;6) and Cribriform (n\u0026thinsp;=\u0026thinsp;1).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBaseline clinicopathological features\u003c/h2\u003e \u003cp\u003eAmong the 239 patients with rST, of which nearly one-third (n\u0026thinsp;=\u0026thinsp;71) originated from cohorts centrally reviewed elsewhere (USA and China), the subtypes included were Apocrine (1.2%, n\u0026thinsp;=\u0026thinsp;77), mixed NST‑ILC (0.9%, n\u0026thinsp;=\u0026thinsp;58), Micropapillary (0.6%, n\u0026thinsp;=\u0026thinsp;36), Mucinous (0.6%, n\u0026thinsp;=\u0026thinsp;35), Cribriform (0.3%, n\u0026thinsp;=\u0026thinsp;22), and Metaplastic (0.2%, n\u0026thinsp;=\u0026thinsp;11) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Several baseline clinicopathological characteristics differed significantly across histology, taking NST as reference. For instance, all rST patients were female, while male cases (n\u0026thinsp;=\u0026thinsp;7) were reported only within NST group. Some geographical and race differences were as well observed. Nearly all Cribriform cases, more frequently diagnosed in Black patients (18.2% vs 1.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), were enrolled from North America (95.5% vs 10.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), a geographical pattern also observed for mixed NST\u0026ndash;ILC (51.7% vs 10.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mucinous cases were less often reported from Europe (28.6% vs 53.7%, p\u0026thinsp;=\u0026thinsp;0.004) (\u003cb\u003eTable S2\u003c/b\u003e). Moreover, Mucinous subtype was characterized by a higher proportion of well or moderately differentiated tumors (64.7% vs 39.3%, p\u0026thinsp;=\u0026thinsp;0.003) and more frequent use of adjuvant ET (81.8% vs 57.5%, p\u0026thinsp;=\u0026thinsp;0.003), consistent with a numerically greater prevalence of estrogen and/or progesterone receptor-positive (ER-positive) disease (71.4% vs 59.4%, p\u0026thinsp;=\u0026thinsp;0.09). Mixed NST\u0026ndash;ILC similarly showed more ER-positive tumors (84.5% vs 57.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), leading to greater ET use (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but also received anthracycline-free adjuvant chemotherapy regimen more often (25.9% vs 4.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and concomitantly with anti-HER2 therapy (74.1% vs 44.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Cribriform cases, likewise, were less often treated with anthracyclines (50% vs 4.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but instead received more frequently carboplatin-containing regimens concomitant with anti-HER2 therapy (100% vs 44.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Patients in the Cribriform subgroup were also more commonly randomized to treatment arms containing lapatinib (95.5% vs 65.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and tended numerically to present with smaller tumors (\u0026le;\u0026thinsp;2 cm: 72.7% vs 45.3%, p\u0026thinsp;=\u0026thinsp;0.009). By contrast, Micropapillary was distinguished only by greater nodal involvement (72.2% vs 51.2%, p\u0026thinsp;=\u0026thinsp;0.001), while Apocrine showed a markedly higher rate of ER-negative tumors (92.2% vs 42.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), translating into less frequent ET (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and, despite otherwise similar features to NST, a higher use of adjuvant RT (84.4% vs 71.2%, p\u0026thinsp;=\u0026thinsp;0.007) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand Table S2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eClinicopathological Comparison of rST and NST.\u003c/b\u003e Summary of major clinicopathological features by histological subtype, with significant differences (in at least one rST compared to NST, taken as the reference) highlighted in bold, based on pairwise comparisons. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.008 (0.05/6) (Bonferroni method) to take into account multiple testing. Absolute numbers are shown, with percentages in parentheses calculated relative to the number of cases within each histological subtype.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHistological grade\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNST\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;5981 (96.2%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAPOCRINE\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;77 (1.2%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMIXED NST-ILC n\u0026thinsp;=\u0026thinsp;58 (0.9%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMICROPAPILLARY\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;36 (0.6%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMUCINOUS\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;35 (0.6%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCRIBRIFORM\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;22 (0.4%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMETAPLASTIC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;11 (0.2%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorly or undifferentiated or cannot be assessed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3617 (60.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (58.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (52.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e12 (35.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (81.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell or moderately differentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2340 (39.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (41.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (47.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e22 (64.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (54.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP.value (NST vs rST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHormone-receptor status\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eER and PgR negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2548 (42.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e71 (92.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9 (15.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eER and/or PgR positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3433 (57.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6 (7.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e49 (84.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (72.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17 (77.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP.value (NST vs rST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymph node involvement (N class)\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot applicable (neoadjuvant chemotherapy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e508 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2411 (40.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e10 (27.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (51.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 (54.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1744 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (29.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9 (25.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (37.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1318 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (27.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e17 (47.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP.value (NST vs rST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant Chemotherapy type\u003c/b\u003e n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3319 (55.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (46.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e15 (25.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (54.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaxane only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2373 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e28 (48.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (34.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e11 (50.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaxane\u0026thinsp;+\u0026thinsp;Carboplatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e289 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e15 (25.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e11 (50.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP.value (NST vs rST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant ET type\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo ET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2541 (42.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e60 (77.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e10 (17.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (41.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e12 (34.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSERM only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1274 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4 (5.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14 (24.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e16 (45.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAI only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1072 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5 (6.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e15 (25.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e6 (17.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSERM\u0026thinsp;+\u0026thinsp;AI only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e458 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3 (3.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7 (12.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLHRH/oophorectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e636 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5 (6.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e12 (20.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1 (2.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP.value (NST vs rST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLegend\u003c/span\u003e: Absolute number (n), percentage (%), rare special histological subtype (rST), Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular breast carcinoma (Mixed NST-ILC), Estrogen Receptor (ER), Progesterone Receptor (PgR), Endocrine therapy (ET), Selective Estrogen Receptor Modulator (SERM), Aromatase Inhibitor (AI), Luteinizing Hormone-Releasing Hormone analogue (LHRH), centimetres (cm).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOutcomes According to Histology\u003c/h3\u003e\n\u003cp\u003eAfter a median follow-up of 9.8 years (interquartile range 6.9\u0026ndash;10.0), no statistically significant differences in disease-free survival (DFS) were observed between NST (reference) and any rST subgroup (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), even after adjustment for major clinicopathological variables (\u003cb\u003eTable S3\u003c/b\u003e). Similarly, overall survival (OS) showed no significant variation across histologies (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Time to central nervous system (CNS) (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) and distant relapse (TTDR) (\u003cb\u003eFigure S2\u003c/b\u003e) equally did not display any meaningful differences. Only numerically better outcomes were observed for Mucinous compared to NST, consistently in terms of DFS (10-years DFS: 89.1% vs 78.1%; adjusted Hazard Ratio [aHR] 0.52, 95% confidential interval [CI] 0.17\u0026ndash;1.62), OS (10-years OS: 96.6% vs 88.2%; aHR 0.41, 95% CI 0.06\u0026ndash;2.93), TTDR (HR 0.51, 95% CI 0.13\u0026ndash;1.96) and time to CNS relapse (HR 0.67, 95% CI 0.09\u0026ndash;4.66). Considering all rST together, both CNS (1.67% vs. 2.14%) and extracranial distant relapse rates (5.8% vs. 9.0%) were numerically lower in comparison with NST (\u003cb\u003eTable S4\u003c/b\u003e). However, when metastatic spread occurred, rSTs showed a numerical greater tendency for visceral involvement (55.5% vs. 44.3%, p\u0026thinsp;=\u0026thinsp;0.35), while fewer soft tissue (5.5% vs. 11.7%, p\u0026thinsp;=\u0026thinsp;0.71) and bone recurrences (16.6% vs. 24.8%, p\u0026thinsp;=\u0026thinsp;0.58) were recorded. Lastly, only Apocrine had a numerically worse time to CNS recurrence (HR 1.48; 95% CI, 0.61\u0026ndash;3.62), although this was not statistically significant.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eOS multivariate analysis.\u003c/b\u003e Multivariate Cox regression model was used to assess the independent association of each histological subtypes with OS; HR with corresponding 95% CI and p-values from Wald tests are reported to assess the strength and statistical significance of each association.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvents/Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e617/6169\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistology\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e599/5933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed NST-ILC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3/58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69 (0.22\u0026ndash;2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApocrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8/76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96 (0.48\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicropapillary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3/36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84 (0.27\u0026ndash;2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7709\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCribriform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13 (0.16\u0026ndash;8.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMucinous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41 (0.06\u0026ndash;2.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetaplastic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.99 (0.49\u0026ndash;8.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMenopausal status at baseline\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostmenopausal or male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e391/3466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226/2703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71 (0.59\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor Size (T class)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192/2794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e425/3375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.67 (1.40\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymph node involvement (N class)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125/2487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135/1804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.51 (1.18\u0026ndash;1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e252/1364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.54 (2.84\u0026ndash;4.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot applicable (Neoadjuvant chemotherapy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105/514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.44 (3.41\u0026ndash;5.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistological Grade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell or moderately differentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e218/2428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorly differentiated, undifferentiated or cannot be assessed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399/3741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12 (0.95\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1761\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHormone receptor status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eER and/or PgR positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e318/3535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eER and PgR negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299/2634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83 (0.64\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant Chemotherapy type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e380/3379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaxane only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214/2470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.68\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaxane\u0026thinsp;+\u0026thinsp;Carboplatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23/320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84 (0.55\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant ET type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo ET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e308/2621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSERM only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122/1317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79 (0.58\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAI only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112/1108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66 (0.49\u0026ndash;0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSERM\u0026thinsp;+\u0026thinsp;AI only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22/467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32 (0.20\u0026ndash;0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLHRH/oophorectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53/656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61 (0.43\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrial planned treatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrastuzumab alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e229/2064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrastuzumab concomitant with Lapatinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194/2058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.71\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrastuzumab followed by Lapatinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194/2047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88 (0.72\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e1\u003c/sup\u003eCovariate\u0026nbsp;Wald\u0026nbsp;p-value;\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLegend\u003c/span\u003e: overall survival (OS); hazard ratio (HR); 95% confidence interval (95% CI), Invasive carcinoma of no special type (NST), Invasive Lobular Breast carcinoma (ILC), Mixed ductal and lobular breast carcinoma (Mixed NST-ILC), Estrogen Receptor (ER), Progesterone Receptor (PgR), Endocrine therapy (ET), Selective Estrogen Receptor Modulator (SERM), Aromatase Inhibitor (AI), Luteinizing Hormone-Releasing Hormone analogue (LHRH).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this retrospective secondary analysis of the large phase III ALTTO trial, we evaluated rST within a large HER2-positive eBC cohort, using centrally reviewed pathology and long-term clinical follow-up. Each rST entity showed distinct baseline clinicopathological profiles compared with NST, although treatment patterns were largely similar. Despite these differences, long-term outcomes were comparable across histologies, with nearly 90% of patients alive at 10 years and no significant differences in DFS or OS between each rST and NST. Substantial discordance was observed in the histological diagnosis assessment for rSTs: upon central review at a high-volume center with dedicated breast pathology expertise, approximately 80% of cases locally diagnosed as rST were reclassified as NST, whereas fewer than 3% of locally diagnosed NST cases were reassigned to a rare subtype.\u003c/p\u003e \u003cp\u003ePrevious studies have consistently reported substantial discrepancies between centralized and local assessments, particularly for tumor grade, extent of residual disease, and HER2 and ER expression \u003csup\u003e\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In contrast, only a limited number of studies have specifically examined inter-observer concordance for histological diagnosis, reporting at best moderate agreement \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. A particularly informative observation comes from the MINDACT trial (NCT00433589), a multicenter phase III study including nearly 7,000 eBC patients, predominantly of luminal-like subtype, in which central pathology review was similarly performed at a reference laboratory \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Only approximately 30% of tumors locally classified as \u0026ldquo;other\u0026rdquo; rare histologies were indeed confirmed upon central review, with a similar pattern observed for ILC, while about 10% of locally diagnosed NST were reclassified as rST \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Consistent with these findings, our results in the HER2-positive scenario further highlight the limited reliability of rST diagnosis in routine local practice and support the need for confirmation at high-volume centers with dedicated breast pathology expertise. This is particularly relevant for subtypes considered prognostically \u0026ldquo;exceptionally\u0026rdquo; favorable, where misclassification could lead to inappropriate treatment de-escalation. Moreover, as the already limited body of evidence on rST largely derives from retrospective studies without central histological confirmation, our results call into question the robustness and reliability of existing data overall. Therefore, if this observation is further validated in other large independent cohorts, it prompts a reconsideration of current pathological diagnostic protocols, including cross-laboratory validation and dedicated training for pathologists. In this regard, digital pathology integrated with artificial intelligence holds promise to substantially improve diagnostic accuracy, reproducibility, and consistency \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn line with previous reported evidence, another key finding of this study is that HER2-positive rSTs exhibit distinct clinicopathological features compared with both their HER2-negative counterparts and HER2-positive NST \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. However, whether analyzed unadjusted or after accounting for these subtype-specific baseline differences, we did not observe a significantly different prognosis for each rSTs in this setting compared to NST. This finding contrasts with prior reports in which HER2-positive rSTs, when analysed collectively, were described as having more favourable outcomes than HER2-positive NST \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Similarly, when individual histological subtypes are examined separately, HER2-positive mucinous tumours have been reported to have more favourable outcomes, despite some inconsistencies and presenting with more aggressive features and exhibiting worse prognosis compared with their HER2-negative counterparts \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. In our cohort, mucinous tumours likewise showed higher 10-year OS (96.6% vs 88.2%) and DFS (89.1% vs 78.1%) compared with NST. In contrast, HER2-positive micropapillary carcinomas have been associated with poorer outcomes than HER2-positive NST \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, whereas apocrine, metaplastic, and mixed NST\u0026ndash;ILC subtypes, consistent with our findings, have previously been described as having survival comparable outcomes \u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Notably, no subtype-specific data have previously been reported for cribriform carcinomas in the HER2-positive setting, likely reflecting the rarity of HER2 positivity in this subtype, yet in our cohort, it also demonstrated outcomes comparable to HER2-positive NST \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, interpretation of these concordant or discordant findings with prior literature remains challenging due to substantial inter-study heterogeneity and methodological limitations, including differing reference groups, limited multivariable adjustment, small sample sizes, variable grouping of distinct histological sub-entities, and temporal or institutional differences in pathological criteria and cut-off definitions for \u0026lsquo;pure\u0026rsquo; rSTs. Consequently, definitive conclusions regarding the prognostic significance of individual HER2-positive rSTs and their implications for possible tailored treatment strategies, distinct from NST, cannot yet be drawn. Along this line, our findings underscore the urgent need for large, dedicated ideally prospective studies using standardized and reliable histological classifications to better uncover this uncertainty. Moreover, in the context of the rapidly evolving peri-operative treatment landscape for HER2-positive eBC, elucidating subtype-specific sensitivity or resistance to novel therapies is equally critical to move beyond the current one-size-fits-all approach \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Future registrational trials on this trajectory should acknowledge the heterogeneity of rSTs by collecting with dedicated effort subtype-specific data rather than grouping these tumors with NST or within a generic \u0026ldquo;other\u0026rdquo; category. Moreover, while a limited number of genomic signatures currently guide treatment decisions in selected NSTs and others are under development specifically in the HER2-positive setting (e.g., HER2DX), their applicability to rSTs remains unknown \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Validating such tools in this context and deeper investigation of their largely unexplored genomic landscape of rSTs, likely responsible for their distinct presentation and behaviour, may enable a shift toward more robust prognostic and predictive stratification beyond histology alone \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e,\u003c/p\u003e \u003cp\u003eOur analysis has several strengths. This study leverages high-quality data from a large phase III trial and represents, to our knowledge, the largest cohort of patients with HER2-positive rST eBC with prospectively collected information. As such, it provides unprecedented insights into a largely unexplored setting, including entities for which evidence had previously been generated (e.g., cribriform carcinoma). The robustness of our findings is further supported by the extended follow-up, with 10-year outcomes reported not only for OS and DFS, but also for TTDR and CNS relapse. A major additional strength lies in the central confirmation of histological diagnoses making this, again to our knowledge, also the largest eBC cohort with centralized histopathological review, a critical aspect given the observed risk of diagnostic discordance. Moreover, while the minor differences between WHO classification editions were incorporated into our analysis, the successive updates of the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) HER2 testing guidelines over the years are unlikely to have had a meaningful impact on our findings.\u003c/p\u003e \u003cp\u003eOn the other hand, one limitation of the study is that central pathological reassessment was performed on a single tumor block per patient. For heterogeneous tumors, this could have led to misclassification if the selected block were not fully representative by reflecting the morphological diversity. Moreover, despite central pathological review being available for most patients (\u0026gt;\u0026thinsp;5,000), approximately one third of the rST cases included were derived from patients without central review. Consequently, some degree of misclassification cannot be excluded, and the true prevalence of rSTs may therefore be lower than reported. To account for this issue, we performed a sensitivity analysis restricted to centrally reviewed cases. Within this subset, analyses were limited to the apocrine subgroup, as it was the only subgroup with \u0026ge;\u0026thinsp;10 survival events, allowing for meaningful comparison. Results were consistent with the primary analysis, showing no significant differences versus NST for either DFS (HR 1.00; 95% CI 0.601\u0026ndash;1.665; p\u0026thinsp;=\u0026thinsp;1.00) or OS (HR 1.14; 95% CI 0.59\u0026ndash;2.20; p\u0026thinsp;=\u0026thinsp;0.69). Indeed, despite the relatively large rST cohort, the very low number of events in the rarest subtypes (\u0026lt;\u0026thinsp;5 in some cases) overall limited statistical power. As such, definitive conclusions should be taken with caution, and a reliable assessment of the potential added benefit of specific adjuvant therapies (e.g., aromatase inhibitors versus tamoxifen) within individual subtypes remains unfeasible. Lastly, given that anti-HER2 peri-operative treatment strategies have evolved substantially over the past decade, the study population may not fully reflect current clinical practice. Nonetheless, patients treated with earlier-generation regimens achieved excellent long-term outcomes, suggesting that many would not have required the newer, more intensive therapies reserved for higher-risk disease.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eALTTO (NCT00490139) was a large-scale international phase III trial that prospectively evaluated escalation of adjuvant trastuzumab-based therapy with the addition of lapatinib, an anti-HER2 tyrosine kinase inhibitor, in HER2-positive eBC. Between June 2007 and July 2011, 8,381 patients were recruited through nearly one thousand centres spanning 44 countries across four continents, using a randomized, open-label design. Briefly, the main aim was to evaluate escalation of adjuvant trastuzumab-based therapy through the addition of lapatinib. The detailed trial design, eligibility criteria, patient characteristics, and main results have been previously described \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. As the lapatinib-alone arm was found to be inferior, it was prematurely closed in 2011 following a protocol amendment, and the 2,.100 patients enrolled in that arm were excluded from the analysis.\u003c/p\u003e\n\u003ch3\u003eHistological Central Review and Regrouping of Study Population\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e graphically illustrates the methodological workflow, outlining the step-by-step process of regrouping and reclassification from initial local histological diagnoses to final categorization. Given the substantial heterogeneity of local histological reports, originating from more than 900 centers across nearly 50 countries, a preliminary harmonization of the original pathology data was first performed under the supervision of an expert BC pathologist (GV). Subsequently, information from the central pathological review was incorporated. This review was conducted across the three dedicated central laboratories, all high-volume institutions with recognized expertise in breast pathology: the European Institute of Oncology (IEO) in Milan, Italy, for most international participants; the Mayo Clinic (Rochester, Minnesota, and Scottsdale, Arizona) for North American patients; and the Peking Union Medical College Hospital for Chinese patients. Each central laboratory received a single representative tumor block per patient and performed a full reassessment, either confirming or reclassifying the local diagnosis, evaluating histological subtype, tumor grade, and HER2/estrogen/progesterone receptor status according to the WHO Breast Tumors Classification (3rd edition) and scoring criteria in use at the time of enrollment. Although central review was carried out for all regions, central histotype data from the U.S. and Chinese cohorts were not included in the dataset available for this analysis; therefore, local pathology reports were used for these cases. To enable robust statistical evaluation and align results with contemporary diagnostic standards, regrouping of all cases into the final analytical categories was then performed by the expert pathologist (GV) on the basis of predefined assumptions (detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and the latest WHO Breast Tumors Classification (5th edition). Finally, pure ILC cases were excluded, as it represents the second most common histological subtype of BC overall and the most frequent ST, and therefore does not fall within the definition of rare entities.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eObjectives and statistical analysis\u003c/h2\u003e \u003cp\u003eThe randomization process, statistical methodology, and endpoints of ALTTO trial have been previously reported \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. The present sub analysis was aimed to explore the baseline clinico-pathological features and long-term outcomes of rST compared to NST (used as reference), in patients with HER2-positive eBC receiving a T-based adjuvant regimen. Patients and tumor baseline features were analysed using descriptive statistics. Differences in continuous variables were assessed with the Wilcoxon or t-test; differences in categorical variables were assessed with the chi-square test or Fisher Exact test. As six rare histologies (apocrine, mixed NST-ILC, micropapillary, mucinous, cribriform and metastatic) were compared to NST, we considered the Bonferroni method for multiple testing, i.e. a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05/6 which is \u0026lt;\u0026thinsp;0.008 as statistically significant. DFS was measured from the date of randomization to the earliest of the following events, including invasive recurrence of BC, diagnosis of a new primary malignancy (contralateral BC or non-breast cancer), or death from any cause. Overall survival corresponded to the time elapsed from randomization until death, irrespective of cause. TTDR was defined as the interval from randomization to the first occurrence of either distant metastatic recurrence or death from any cause, whichever occurred first. Time to CNS recurrence was defined as the interval from randomization to the first documented occurrence of CNS metastasis or death from any cause, whichever occurred first. Survival functions were estimated using the Kaplan‑Meier method. Adjusted HR with 95% CI and covariate‑Wald p‑values were calculated using a multivariate Cox regression model, adjusting for menopausal status at baseline, tumor size, lymph node involvement, grade, adjuvant chemo, adjuvant endocrine therapy and the randomization arm. TTDR and time to CNS recurrence were analyzed using cumulative incidence functions. Due to the very small number of events/cases in the rare histology groups (DFS, OS, CNS and TTDR), the survival analyses are exploratory and the statistical power to detect any difference is very low.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRiccardo Gerosa and Guilherme Nader-Marta contributed to the conceptualization, data curation, writing of the original draft, and to review and editing. Ameye Lieveke contributed to data curation and formal analysis and to writing, review and editing. Giuseppe Viale contributed to conceptualization, data curation, and to writing, review and editing. All other authors (Diogo Martins-Branco, Marianne Paesmans, Philippe Aftimos, Armando Santoro, Anup Choudhury, Marco Colleoni, Martine Piccart-Gebhart, Evandro de-Azambuja) contributed to the writing of the manuscript, review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;We thank each and every one of the patients who participated in the Adjuvant Lapatinib and/or Trastuzumab Treatment Optimisation (ALTTO) study; the Breast European Adjuvant Study Team (BrEAST) Data Center; the Frontier Science (FS) team; the Breast International Group (BIG) headquarters; the US National Cancer Institute (NCI); the North Central Cancer Treatment Group (NCCTG; now part of the Alliance for Clinical Trial in Oncology); the ALTTO Executive and Steering Committee members; the Independent Data Monitoring Committee (IDMC) members; the Cardiac Advisory Board members; the three central pathology laboratories; GlaxoSmithKline; Novartis; physicians, nurses, trial coordinators and pathologists. We thank from BIG: Celine Schurmans, Orsolya Birta, Amal Arahmani, Theodora Goulioti, Panayota Boussis; from BrEAST: Daniela D. Rosa, Kamal Saini, Otto Metzger Filho, Sébastien Guillaume, Sylvia Napoleone and Christophe Lecocq; from FS: Robin McConnell, Vicki Paterson, Christine Campbell, Eleanor McFadden, Emma Paterson, Faye Samy and Garrick Kassab for their scientific, statistics and/or project management support. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from 19\u003csup\u003eth\u003c/sup\u003e November 2024, but restrictions apply to the availability of these data, which were used under licence for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of BIG and Institute Jules Bordet.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant number from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable to the present exploratory study. All patients provided written informed consent to participate in the ALTTO trial. Institutional review board or ethics committee approval was obtained and was mandatory for all participating centers. The study was conducted in accordance with ethical standards and the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests: \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eR. Gerosa: meeting/travel support grants: Novartis, Daiichii Sankyo, Lilly, Menarini\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eG. Nader Marta: Meeting/travel grants to attend medical conference: AstraZeneca\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eD. Martins-Branco reports employment with the European Society for Medical Oncology (ESMO) since September 1, 2023; participation as medical research fellow in research studies institutionally funded by Eli Lilly, F Hoffmann-La Roche Ltd and Novartis to Institute Jules Bordet (2021-2023); and non-financial interests as past member of the Board of Directors for the Associação de Investigação e Cuidados de Suporte em Oncologia (2022-2024) and member of the American Society of Clinical Oncology, Associação Portuguesa de Cuidados Paliativos, Multinational Association of Supportive Care in Cancer and Sociedade Portuguesa de Oncologia\u003c/li\u003e\n \u003cli\u003ePAftimos: Consulting: Boehringer Ingelheim, Macrogenics, Roche, Novartis, Amcure, Servier, G1 Therapeutics, Radius, Deloitte, Daiichi Sankyo, Olema. Honoraria: Synthon, Amgen, Novartis, Gilead, Lilly, Menarini. Travel grants: Amgen, MSD, Pfizer, Roche, Daiichi Sankyo. Research funding to my institution: Roche\u003c/li\u003e\n \u003cli\u003eA Santoro: consulting or advisory roles for Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp \u0026amp; Dohme, Sanofi, and Incyte; and participation in speakers bureaus for Takeda, Roche, AbbVie, Amgen, Celgene, AstraZeneca, Lilly, Sandoz, Novartis, Bristol Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, Merck Sharp \u0026amp; Dohme, and ArQule\u003c/li\u003e\n \u003cli\u003eG. Viale: Financial Interests, Personal, Advisory Board: Roche, AstraZeneca, Daiichi Sankyo, MSD Oncology, Pfizer; Financial Interests, Personal, Other, Consulting fees: Agilent; Financial Interests, Personal, Invited Speaker: Gilead; Financial Interests, Personal, Other, Educational webinar: Medscape; Financial Interests, Institutional, Invited Speaker: AstraZeneca; Financial Interests, Institutional, Research Grant: Roche.\u003c/li\u003e\n \u003cli\u003eM. Lambertini: advisory role for Roche, Lilly, Novartis, AstraZeneca, Pfizer, Seagen, Gilead, MSD, Pierre Fabre, Menarini, Exact Sciences, Nordic Pharma; speaker honoraria from Roche, Lilly, Novartis, Pfizer, Sandoz, Libbs, Daiichi Sankyo, Takeda, Ipsen, Menarini and AstraZeneca; travel grants from Gilead, Roche, and Daiichi Sankyo; research funding (to his institution) from Gilead; nonfinancial interests as a member of the national council of the Italian Association of Medical Oncology (AIOM)\u003c/li\u003e\n \u003cli\u003eA. Choudhury: Financial Interests, Personal, Other, Working as a full time Clinical Development Medical Director and company stocks provided as per compensation plan: Novartis Healthcare Pvt. Ltd\u003c/li\u003e\n \u003cli\u003eM.A. Colleoni: Non-Financial Interests, Personal, Other, Co-Chair Scientific Committee: International Breast Cancer Study Group\u003c/li\u003e\n \u003cli\u003eM. Piccart: Board Member Scientific Board: Oncolytics. Consultant (honoraria): AstraZeneca, Gilead, Lilly, Menarini, Mersana, MSD, Novartis, Pfizer, Roche-Genentech, Seattle Genetics, Seagen, NBE Therapeutics, Summit Therapeutics Research grants to my Institute : AstraZeneca, Lilly, Menarini, MSD, Novartis, Pfizer, Roche-Genentech, Servier, Gilead\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eE. de Azambuja: Financial Interests, Personal, Advisory Board: Roche/GNE, Novartis,SeaGen, MSD; Financial Interests, Personal, Invited Speaker: Zodiac, Libbs, Pierre Fabre, Lilly, AstraZeneca, Gilead Sciences; Financial Interests, Personal, Other, Chair of the Gilead Sciences Research Scholars Program in Solid Tumours: Gilead Sciences; Financial Interests, Personal, Other, Roche WO43571 IDMC: Roche/Genentech; Financial Interests, Institutional, Research Grant: Roche/GNE, AstraZeneca, GSK/Novartis, Servier; Financial Interests, Institutional, Other, Travel Grant: Roche/GNE; Financial Interests, Institutional, Invited Speaker: MSD, ABCSG, Nektar, Gilead, Immunomedics, Synthon, Odonate Therapeutics; Financial Interests, , Invited Speaker, ASCENT 04: Gilead; Financial Interests, , Invited Speaker, Aphinity, Lorelei, \u0026nbsp; Impassion03: Roche; Financial Interests, , Invited Speaker, AURORA: Breast International Group; Financial Interests, , Invited Speaker, Olympia: AstraZeneca; Financial Interests, Personal, Other, Travel grant: AstraZeneca; Financial Interests, Personal, Other, Travel Grant SABCS 2024: Gilead; Financial Interests, Institutional, Other, Scholarship grant for 2025-2026 for Luca Arecco: Gilead Sciences; Financial Interests, Institutional, Invited Speaker, Research grant for the TUCANIBE retrospective study: Pfizer; Non-Financial Interests, , Advisory Role, Member of the cardio-oncology council: European Society of Cardiology (ESC), Belgian Society of Cardiology; Non- Financial Interests, , Advisory Role, Belgium governmental institution for cancer: KCE; Non-Financial Interests, , Other, Editorial board member: ESMO Open; Non-Financial Interests, , Advisory Role: Anticancer Fund; Non-Financial Interests, Leadership Role, President 2023-2026: Belgian Society of Medical Oncology (BSMO)\u003c/li\u003e\n \u003cli\u003eAll other authors declare not conflict of interest related to the manuscript\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel, R. 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Journal of Clinical Oncology 34, 1034\u0026ndash;1042 (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-breast-cancer","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjbcancer","sideBox":"Learn more about [npj Breast Cancer](http://www.nature.com/npjbcancer/)","snPcode":"41523","submissionUrl":"https://mts-npjbcancer.nature.com/","title":"npj Breast Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Early breast cancer, HER2-positive, Central Pathology Review, Mucinous carcinoma, Apocrine carcinoma, Micropapillary carcinoma, Cribriform carcinoma, Metaplastic carcinoma, Mixed NST-ILC","lastPublishedDoi":"10.21203/rs.3.rs-9082124/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9082124/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRare special histological subtypes (rST) account for ~10% of early-stage breast cancer (eBC) but their prognostic value remains poorly defined, particularly in HER2-positive disease. This sub-analysis of patients with HER2-positive eBC treated with adjuvant trastuzumab-based therapy in the ALTTO trial (NCT00490139) aims to compare baseline characteristics and clinical outcomes between patients with rST (n=239) and those with invasive carcinoma of no special type (NST, n=5,981). Among the cases with central histopathological review (n=5,302), 82% of locally diagnosed rST cases were reclassified as NST. When adjusted for baseline differences between different rST and NST, the histological subtype was not associated with survival outcomes. Non-significant trends of better outcomes were observed for mucinous subgroup (n=35) (10-year OS: 96.6% vs 88.2%, aHR 0.41, 95%CI 0.06–2.93). Although rST did not have independent prognostic value in HER2-positive eBC setting, the high diagnostic discordance raises concerns about existing evidence supporting differential management according to rST.\u003c/p\u003e","manuscriptTitle":"Rare Special Breast Cancer Histologies in the ALTTO Trial: Central Histology Review and Outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-05 17:09:26","doi":"10.21203/rs.3.rs-9082124/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-04T02:28:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237323996661226172854130675950429870279","date":"2026-04-07T20:05:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T19:03:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102051127502650792906293173471973843150","date":"2026-03-31T12:39:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-31T08:29:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T08:11:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-24T04:08:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Breast Cancer","date":"2026-03-10T09:30:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-breast-cancer","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjbcancer","sideBox":"Learn more about [npj Breast Cancer](http://www.nature.com/npjbcancer/)","snPcode":"41523","submissionUrl":"https://mts-npjbcancer.nature.com/","title":"npj Breast Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9841c65d-6a1a-4472-a4df-daeb18d06baf","owner":[],"postedDate":"April 5th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-04T02:28:14+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65469145,"name":"Biological sciences/Cancer"},{"id":65469146,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-04-05T17:09:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-05 17:09:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9082124","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9082124","identity":"rs-9082124","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}