Tumor growth rate of invasive breast cancers during wait times for surgery assessed by ultrasonography.

Several studies suggest that delay in the surgical treatment of breast cancer is significantly associated with lower survival. This study evaluated the tumor growth rate (TGR) of invasive breast cancers during wait times for surgery quantitatively using ultrasonography (US) and identified clinicopathologic factors associated with TGR.This retrospective study was approved by our institutional review board and the requirement for written informed consent was waived. Between August 2013 and September 2014, a total of 323 unifocal invasive breast cancers in 323 women with serial US images at the time of diagnosis and surgery were included. Tumor diameters and volumes were measured using 2-orthogonal US images. TGR during wait times for surgery was quantified as specific growth rates (SGR; %/day) and was compared with clinicopathologic variables using univariate and multivariate analyses.Median time from diagnosis to surgery was 31 days (range, 8-78 days). Maximum tumor diameters and volumes at the time of surgery (mean, 15.6 mm and 1.6 cm) were significantly larger than at diagnosis (14.7 mm and 1.3 cm) (P < 0.001). On multivariate analysis, surrogate molecular subtype was a significant independent factor of SGR (P = 0.001); triple negative cancers showed the highest SGR (1.003%/day) followed by HER2-positive (0.859 %/day) and luminal cancers (luminal B, 0.208 %/day; luminal A, 0.175%/day) (P < 0.001). Clinical T stage was more frequently upgraded in nonluminal (triple negative, 18% [12/67]; HER2-positive, 14% [3/22]) than luminal cancers (luminal B, 3% [1/30]; luminal A, 2% [4/204]) (P < 0.001).Invasive breast cancers with aggressive molecular subtypes showed faster TGR and more frequent upgrading of clinical T stage during wait times for surgery.

Introduction

Breast cancer patients typically wait weeks before surgery for preoperative work-up, consideration of options such as reconstruction, and referral to tertiary care centers.[ Wait times for breast cancer surgery have increased over the past decade.[ Delay between diagnosis and surgery can cause anxiety in women with breast cancer over concerns of interim tumor progression. Indeed, several studies have reported that a delay in the surgical treatment of breast cancer is significantly associated with lower survival.[ Accordingly, the wait time for surgery has recently been proposed as a quality indicator in breast cancer care as it is an important contributor to patient satisfaction and cancer outcomes.[ At present, there is no established benchmark for the wait time before breast cancer surgery, although a period of ≤30 days is considered to be a modest delay with better prognosis compared to wait times of longer intervals.[ In addition, Wagner et al[ has reported that a modest time interval between diagnosis and surgery is not significantly associated with tumor size progression.

However, breast cancer is a highly heterogeneous disease with variable biological features and clinical outcomes.[ Therefore, it is natural for breast cancers to have varying growth rates according to the characteristics of patients and tumors.[ A previous study evaluated the tumor growth rate of breast cancers before diagnosis and demonstrated that intrinsic tumor growth rates were different according to the molecular subtype with triple-negative tumors showing the fastest growth.[ Therefore, we hypothesized that different molecular subtypes of breast cancers may also affect tumor progression, defined as an increase in size, during wait times for surgery after diagnosis and that the fast-growing tumors may show a considerable change in size over a short time interval. Ultrasonography (US) is an accurate method for measuring tumor size and repetitive evaluation is feasible because of its nonionizing technique. By comparing tumor sizes on serial follow-up US images, quantitative parameters of tumor growth rates can be derived including the tumor volume doubling time (TVDT) and specific growth rate (SGR).[ SGR has been proposed as a more suitable parameter than TVDT for shorter time intervals, for all tumor volume changes including both increases and decreases, and for statistical testing.[

The purpose of our study, therefore, was to quantitatively evaluate the tumor growth rate of invasive breast cancers during wait times for surgery using US and to identify clinicopathologic factors associated with tumor growth rates.

Materials and methods

Patients and Lesions

This retrospective study was approved by our institutional review board and the requirement for written informed consent was waived. A search of our database identified 1328 consecutive women diagnosed with invasive breast cancers who had undergone primary surgical treatment at Seoul National University Hospital between August 2013 and September 2014. Among them, 1118 women had available serial breast US images at the time of diagnosis and surgery. From this population, we excluded women who were not eligible for tumor growth rate assessment with US for the following reasons: multifocal or diffuse cancers on pathologic examination[ owing to the difficulty in correlating tumor sizes on US and pathology (n = 402), vacuum-assisted core needle biopsy or surgical excisions performed before definitive surgery (n = 214), unavailability of 2-orthogonal image sets with the same probe direction on serial US examinations (n = 135), and poor visibility of lesions on US (n = 44). Finally, 323 unifocal invasive breast cancers in 323 women with serial 2-orthogonal US image sets constituted our study population.

US examinations

All women underwent breast US examinations at both diagnosis and surgery. Initial US examinations were performed as a first diagnostic imaging either at our institution (n = 123) or outside referring facilities (n = 200). The second US images were acquired 1 day before surgery in all women according to the routine protocol of our institution. All breast US examinations at our institution were performed by 1 of 5 radiologists with 2 to 8 years of experience using the Aixplorer system (Supersonic Imagine, Aix en Provence, France) with a 15- to 4 MHz linear-array transducer or HI VISION Preirus (Hitachi Medical Systems, Tokyo, Japan) with a 13- to 5 MHz linear-array transducer. For the US examinations performed at outside referring facilities, various scanners equipped with a high-resolution linear array transducer with a center frequency of at least 10 MHz were used fulfilling the American College of Radiology practice parameters[ and all examinations were performed by physicians board certified in radiology with varying degrees of experience. At least 2-orthogonal images were acquired in either the transverse/longitudinal or radial/anti-radial planes for each breast mass and the same probe directions were applied for the serial US examinations. All images were sent and saved to a picture archiving and communication system (PACS) in digital imaging and communications in medicine (DICOM) file format.

Tumor diameter measurement and calculation of tumor growth rates

Three breast radiologists (YK, SHL, WKM) independently measured the tumor diameters using serial US images on PACS workstations. All readers were fellowship trained in breast imaging and had an average of 8.7 years of experience (range, 1–20 years) in breast US examinations. A set of 2-orthogonal images of each tumor were provided for the readers in random order regardless of the time sequence. Three perpendicular tumor diameters (referred to as a, b, and c) were measured using electronic calipers and then were used to estimate the tumor volume using the formula for oblate spheroids[: V = 4/3π • a/2 • b/2 • c/2, where a, b, and c denote the longest diameter of a lesion, the maximum perpendicular diameter in the same plane, and the longest vertical diameter in the orthogonal plane, respectively.[ The tumor growth rate between diagnosis and surgery was quantified using the parameter of specific growth rate (SGR, %/day) calculated using the following equation:[ SGR = ln (V2/V1)/(t2 – t1), where V1 and V2 are the tumor volumes at the time of diagnosis (t1) and surgery (t2), respectively.

Data collection

All clinicopathologic data were obtained from our prospectively maintained web-based database. The clinical data collected included the patients’ age at diagnosis, menopausal status, presence or absence of palpable symptoms, a personal or first-degree family history of breast cancer, mammographic breast density and findings according to the Breast Imaging Reporting and Data System (BI-RADS),[ initial tumor size on US, biopsy needle gauge, number of acquired samples on US-guided core needle biopsy, length of time between diagnosis and surgery, and type of breast surgery. Pathologic data collected included the histologic type of breast cancer, invasive tumor size, histologic grade according to the Nottingham Grading System,[ presence or absence of carcinoma in situ components, lymphovascular invasion, and axillary lymph node metastasis. Tumor stage was classified according to the American Joint Committee on Cancer 7th edition.[ Immunohistochemical (IHC) staining was performed for hormone receptor (HR) (estrogen receptor and progesterone receptor), human epidermal growth factor receptor 2 (HER2), and Ki-67 using standard methods as previously described.[ Fluorescence in situ hybridization for HER2 DNA amplification assessment was performed in all equivocal cases with HER2 IHC 2+ cases. Surrogate molecular subtypes were classified on the basis of their HR, HER2, and Ki-67 status: luminal A (HR-positive, Ki-67 low, and HER2-negative), luminal B (HR-positive, Ki-67 high, and HER2-negative or HR-positive, any Ki-67, HER2-positive), HER2-positive (HR-negative and HER2-positive), and triple negative (HR-negative and HER2-negative).[

Statistical analysis

Interobserver agreement among the three readers regarding the measurement of tumor diameters, tumor volumes, and SGR was evaluated using intraclass correlation coefficient (ICC) values. An ICC of 0.00–0.20 indicates slight agreement; 0.21–0.40, fair agreement; 0.41–0.60, moderate agreement; 0.61–0.80, substantial agreement; and 0.81–1.00, almost perfect agreement.[ Median tumor diameters measured by the three readers were determined for each lesion and were used to calculate the tumor volumes and SGR. Tumor diameters and volumes acquired at the two time points of diagnosis and surgery were compared using the paired samples t-test. The association between clinicopathologic variables and SGR was evaluated using the independent samples t-test or analysis of variance with a post-hoc Tukey test. Multiple linear regression analysis was performed to determine the variables independently associated with SGR. Changes in tumor diameters and clinical T stages determined on serial breast US examinations were compared according to the clinicopathologic variable using analysis of variance or Fisher exact test, as appropriate. Correlation and agreements between the tumor diameters on breast US and pathology were evaluated using Pearson correlation coefficient and Bland–Altman analysis. Two-tailed P values of <0.05 were considered to indicate a statistically significant difference. All statistical analyses were performed using SPSS software (PASW Statistics, version 20; SPSS Inc, Chicago, IL).

Results

Measurement of tumor diameters, tumor volumes, and the specific growth rate

The 3 readers showed almost perfect agreement for the measurement of tumor diameters (range of ICCs, 0.892–0.955), tumor volumes (0.927–0.964), and SGR (0.862) (Table 1). The median tumor diameters and volumes at the time of surgery (a2, 15.6 ± 6.6 mm [mean ± standard deviation]; b2, 10.0 ± 4.1 mm; c2, 13.0 ± 5.5 mm; V2, 1.6 ± 2.0 cm3) were significantly larger than those at the time of diagnosis (a1, 14.7 ± 6.1 mm; b1, 9.7 ± 3.7 mm; c1, 12.4 ± 5.0 mm; V1, 1.3 ± 1.5 cm3) (P < 0.001, all). SGR calculated using median tumor diameters and volumes at the time of diagnosis and surgery was a mean of 0.337 ± 1.067 %/day (range, −3.954 to 4.678 %/day).

Table 1

Interobserver agreements between the three readers regarding the measurement of tumor diameters, tumor volumes, and specific growth rates.

Clinical, imaging, and pathologic characteristics

The median age of women was 53 years (range, 27–82 years). Among the 323 women with 323 invasive breast cancers, 162 (50%) presented with palpable symptoms and the other 161 (50%) were detected by screening examinations. A personal history and family history of breast cancer were present in 3% (10/323) and 7% (24/323) of women, respectively. Mammography was performed in all women and showed a breast tissue composition of dense (BI-RADS grade c–d) in 72% (234/323) and non-dense (BI-RADS grade a–b) in 28% (89/323) of women. Mass or asymmetry without microcalcification was the most common mammographic finding (65% [210/323]). Percutaneous needle biopsy was performed using a 14-gauge core needle with a mean number of core samples of 5 (range, 3–8). The median time from initial imaging to surgery was 31 days (range, 8–78 days). Breast-conserving surgery was performed in 81% (262/323) of women and the other 19% (61/323) underwent total mastectomy. The majority of breast cancers were invasive ductal carcinomas, not otherwise specified type (88% [283/323]), 73% (237/323) were pathologic T stage 1, and 81% (261 of 323) did not have involved axillary lymph nodes. The histologic grade was low to intermediate in 60% (194/323) and high in 40% (129/323) of cases. The most common surrogate molecular subtype was luminal A (63% [204/323]), followed by triple negative (21% [67/323]), luminal B (9% [30/323]), and HER2-positive (7% [22/323]) (Table 2).

Table 2

Specific growth rates of 323 invasive breast cancers according to clinicopathologic factors.

Clinicopathologic factors associated with specific growth rate

Among the clinicopathologic factors, a palpable symptom at diagnosis, pathologic T stage, histologic grade, HR status, Ki-67 expression, and surrogate molecular subtype were significant factors associated with SGR on univariate analysis (P < 0.05) (Table 2). Palpable cancers showed higher SGR than nonpalpable cancers (P = 0.005). Higher pathologic T stage and histologic grade were significantly associated with higher SGR (P < 0.001, both). Among the IHC factors, negative HR status and high Ki-67 level were associated with higher SGR (P < 0.001, both). Whereas, HER2 status was not significantly associated with SGR. Triple negative breast cancers showed the highest SGR followed by HER2-positive and luminal (luminal B and luminal A) breast cancers (P < 0.001). The difference in SGR between triple negative and HER2-positive breast cancers was not statistically significant (P = 0.939). Luminal A breast cancers showed significantly lower SGR than triple negative (P < 0.001) and HER2-positive breast cancers (P = 0.015). Luminal B breast cancers showed significantly lower SGR than triple negative cancers (P = 0.002) and showed a trend toward lower SGR than HER2-positive breast cancers (P = 0.101).

Parameters showing statistical significance on univariate analysis were used as input variables for multiple linear regression analysis. Among the 6 variables, collinearity was observed between 2 predictor variables of HR status and surrogate molecular subtype (r = −0.955, P < 0.001), as expected, because the surrogate molecular subtype is mainly determined by HR status. Therefore, 2 different models were used to evaluate the association between clinicopathologic factors and SGR. HR status and surrogate molecular subtype showed an independently significant relationship with SGR in each model (Table 3).

Table 3

Multiple linear regression analysis to evaluate the association between clinicopathologic factors and specific growth rates of invasive breast cancers.

Tumor diameter changes on serial breast US and comparison with pathology

Changes in maximum tumor diameters between initial and second US images were significantly different among the molecular subtypes (P < 0.001) (Table 4). Breast cancers with more aggressive molecular subtypes showed larger diameter changes (triple negative, 2.1 ± 2.6 mm; HER2-positive, 1.9 ± 2.0 mm) than luminal breast cancers (luminal B, 0.6 ± 2.4 mm; luminal A, 0.4 ± 1.6 mm) (P < 0.005 for triple negative vs. luminal subtypes; P = 0.005 for HER2-positive vs. luminal A; P = 0.110 for HER2-positive vs. luminal B). The clinical T stage determined by breast US was more frequently upgraded from T1 to T2 during wait times for surgery in nonluminal breast cancers (14% [3/22] for HER2-positive and 18% [12/67] for triple negative cancers) than in luminal cancers (luminal B, 3% [1/30]; luminal A, 2% [4/204]) (P < 0.001) (Figs. 1 and 2).

Table 4

Changes in maximum tumor diameters and clinical T stage during wait times for surgery according to surrogate molecular subtype.

Figure 1

A 53-year-old woman with an invasive ductal carcinoma in the left breast 12 o’clock location detected on screening US examination. On initial US images (A, B) acquired on the same day of core needle biopsy, maximum tumor diameter and volume were 17.1 mm and 2.56 cm3, respectively. On the second US images (C, D) acquired 1 day before surgery and 21 days after the initial US, the tumor size did not change significantly but only with biopsy changes in and around the tumor (arrows). Maximum tumor diameter and volume were measured as 18.5 mm and 2.58 cm3, respectively. The calculated SGR was 0.045 %/day. On pathologic examination, the invasive tumor size was 18 mm (pT1) with a histologic grade 3, HR-positive, HER2-negative, low Ki-67 (1%), and luminal A subtype. HER2 = human epidermal growth factor receptor 2, HR = hormone receptor, SGR = specific growth rate; US = ultrasound.

Figure 2

A 31-year-old woman with an invasive ductal carcinoma in the left breast 11 o’clock location presented with a palpable lump. On initial US images (A, B) acquired on the same day of core needle biopsy, maximum tumor diameter and volume were 17.8 mm and 2.53 cm3, respectively. On the second US images (C, D) acquired 1 day before surgery and 40 days after the initial US, the tumor size increased considerably. Maximum tumor diameter and volume were measured as 23.3 mm and 4.70 cm3, respectively. The calculated SGR was 1.552 %/day. On pathologic examination, the invasive tumor size was 25 mm (pT2) with a histologic grade 3, HR-negative, HER2-negative, high Ki-67 (15%), and triple negative subtype. HER2 = human epidermal growth factor receptor 2, HR = hormone receptor, SGR = specific growth rate; US = ultrasound.

Correlations and agreements between maximum tumor diameters measured on breast US and pathology are shown in Figure 3. There was a trend toward slightly better correlation and agreement in tumor diameter between the second US and pathology than between the initial US and pathology. The mean difference in tumor diameter between initial US and pathology (initial US diameter – pathologic diameter) was −2.9 ± 4.7 mm, and between second US and pathology (second US diameter – pathologic diameter) was −2.0 ± 4.6 mm. The diameter difference between initial US and pathology was not different according to surrogate molecular subtype (triple negative, −3.9 ± 5.5 mm; HER2-positive, −1.5 ± 3.6 mm; luminal B, −3.6 ± 5.3 mm; and luminal A, −2.6 ± 4.4 mm) (P = 0.117).

Figure 3

Correlations and agreements between maximum tumor diameters measured on breast US and pathology. Both maximum tumor diameters measured on initial US (A) and second US (B) showed strong linear correlations with invasive tumor size on pathology with slightly higher correlation coefficients for the second US (r = 0.780) than the initial US (r = 0.758). On Bland–Altman plots, the mean difference (solid lines) between maximum tumor diameters on US and pathology was 2.9 mm for initial US (C) and 2.0 mm for second US (D). The range between 95% limits of agreement (dashed lines) was 18.6 mm for the initial US (C) and 18.0 mm for the second US (D).

Discussion

In our study, the tumor growth rate of invasive breast cancers during wait times for surgery quantified as SGR was significantly associated with surrogate molecular subtypes (P = 0.001). Triple negative breast cancers showed the fastest growth rates followed by HER2-positive breast cancers. Those nonluminal breast cancers, which are more aggressive forms of breast cancer, showed greater changes in maximum tumor diameters between diagnosis and surgery than luminal breast cancers causing more frequent upgrading of the clinical T stage as determined by US. The results of our study are consistent with a previous study, which reported the fastest growth rates in triple negative breast cancers with a shorter sojourn time.[ To the contrary, a recent study by Yoo et al,[ which calculated SGR using 2 time point tumor sizes on US before surgery, reported that SGR did not significantly differ according to the molecular tumor subtype. However, they used only 1 dimension of tumors based on the medical records for the calculation of SGR assuming that the tumor shape was a sphere. In our study, 3 perpendicular diameters of tumors on 2-orthogonal US images were independently measured by 3 radiologists and a meticulous comparison of serial US images in the same probe directions was performed. In addition, our study consistently compared the tumor diameters between the patients’ initial diagnostic images, not the one performed at the initial visit to a tertiary care center and second images performed 1 day before surgery. Therefore, we were able to obtain information on how much the tumor diameters had changed during wait times for surgery from the patients’ perspective.

With regard to the interobserver agreement for tumor diameter measurement, almost perfect agreement was found among the 3 radiologists (ICC, 0.892–0.955). It is known that tumor size assessment by US is accurate and is well correlated with pathologic tumor size, although US slightly underestimates tumor size.[ In our study, the second US examinations are performed after percutaneous core needle biopsy. Despite concerns over the biopsy effect, which may hamper accurate size measurements, there was a trend toward slightly better correlation between the second US size and pathologic size (r = 0.758) than between the initial US size and pathologic size (r = 0.780). In addition, the difference in tumor diameters with pathology was slightly smaller for the second US (2.0 ± 4.6 mm) than the initial US (2.9 ± 4.7 mm).

The degree of tumor diameter change between diagnosis and surgery (2.1 ± 2.6 mm for triple negative breast cancers and 0.4 ± 1.6 mm for luminal A breast cancers) as well as the tumor diameter difference between US and pathology (2.9 ± 4.7 mm for initial US vs. pathology and 2.0 ± 4.6 mm for second US vs. pathology) was very small in our study. This may have been because of the relatively short time interval between diagnosis and surgery (median, 31 days; range, 8–78 days) at our institution.[ A previous study by Wagner et al[ used the difference between the initial imaging size and pathologic size as a surrogate for tumor size progression and reported that the median difference from baseline sonographic tumor size to surgery was 1 mm (range, 75 mm smaller to 83 mm larger at surgery) with modest time intervals. However, they pointed out that assessing the change in tumor size as measured by imaging at diagnosis to the size on imaging immediately before surgery may allow more uniform comparison of disease progression. At our institution, preoperative breast US is routinely performed 1 day before surgery in all breast cancer patients to mark accurate disease extent. Therefore, we can compare tumor diameters on serial US images acquired at the time of diagnosis and surgery and thereby calculate tumor growth rates during wait times for surgery. According to our results, breast cancers showed different growth rates according to the tumor characteristics, although the tumor size change was small in the short time interval. Breast cancers having fast tumor growth rates may present marked tumor progression if the surgery is delayed longer than usual. Therefore, efforts to reduce wait times for surgery should be pursued especially for breast cancers with high tumor growth rates such as triple negative or HER2-positive breast cancers, which may be discriminated from luminal breast cancers through IHC staining for HR status or characteristic imaging features at diagnosis.[

Our study has several limitations. First, this was a retrospective study performed at a single center, and as we excluded patients who had received neoadjuvant chemotherapy or patients with multifocal or diffuse breast cancers, more advanced stage cancers were not evaluated. Second, we did not evaluate the interobserver variability of US data acquisition. Variability within data acquisition could occur as a result of minor changes in patient's position or the degree of compression. Therefore, we only included cases with serial US image sets in the same probe direction to reduce the bias from inadequate data acquisition. As automated 3-dimensional US scanners are currently installed in many institutions, they could be used to monitor changes in tumor diameter and tumor volumes during wait times for surgery.[ Lastly, the patient series reported in this study was relatively recent with insufficient follow-up data. This reflects our current practice, but does not allow us to determine the effect of tumor growth rates on the patients’ long-term outcomes of disease-free and overall survival. In this regard, however, a recent study by Yoo et al[ demonstrated that SGR measured by US was associated with disease-free survival in breast cancer patients, particularly in the subgroup of patients with an initial tumor size >2 cm.

In conclusion, invasive breast cancers with aggressive molecular subtypes showed faster tumor growth rates and more frequent upgrading of clinical T stage during wait times for surgery. Therefore, it is highly desirable to minimize wait times for surgery in breast cancer patients particularly with triple negative or HER2-positive molecular subtypes.

Acknowledgments

We would like to thank Chris Woo, B.A., for his kind assistance in editing this manuscript.