Concordance assessment of Watson for Oncology in breast cancer chemotherapy: first China experience
Original Article

Concordance assessment of Watson for Oncology in breast cancer chemotherapy: first China experience

Hong Pan1#, Jing Tao1,2#, Mengjia Qian1#, Wenbin Zhou1, Yi Qian1, Hui Xie1, Shengqi Jing3,4, Tingyu Xu3,4, Xin Zhang3,4, Zuolei Dai3,4, Mingliang You5, Yun Liu3,4, Xiaoan Liu1, Shui Wang1

1Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China; 2Department of General Surgery, The Fourth Affiliated Hospital of Nanjing Medical University (Nanjing Pukou Hospital), Nanjing 210031, China; 3Department of Information, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China; 4Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing 210029, China; 5Hangzhou Cognitive Care, Hangzhou Artificial Intelligence Industrial Park, Hangzhou 310000, China

Contributions: (I) Conception and design: H Pan, Y Liu, X Liu, S Wang; (II) Administrative support: S Jing, M You; (III) Provision of study materials or patients: Y Qian, H Xie, T Xu, X Zhang; (IV) Collection and assembly of data: M Qian, W Zhou, S Jing; (V) Data analysis and interpretation: H Pan, J Tao, M Qian, W Zhou, Z Dai; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Dr. Yun Liu. Department of Information, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China. Email: liuyun@njmu.edu.cn; Dr. Xiaoan Liu. Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China. Email: liuxiaoan@126.com; Prof. Dr. Shui Wang. Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China. Email: ws0801@hotmail.com.

Background: IBM Watson for Oncology (WFO) is an artificial intelligence cognitive computing system that provides confidence-ranked, evidence-based treatment recommendations for cancer. We examine the level of agreement for breast cancer chemotherapy between WFO recommended and clinical use in a large population of breast cancer cases.

Methods: A total of 1,301 breast cancer patients were reviewed in The First Affiliated Hospital with Nanjing Medical University, China from June 2013 to December 2017. Patients’ data were entered manually into WFO by the trained senior oncology fellows. Chemotherapy recommendations were provided in 3 categories, “Recommended”, “For Consideration”, and “Not Recommended”. Concordance was achieved when oncologists’ treatment suggestions were in the “Recommended” or “For Consideration” categories.

Results: The chemotherapy regimen concordance was 69.4% among all breast cancer cases, 65.0% among the cases in adjuvant chemotherapy (AC) group and 96.7% among the cases in neoadjuvant chemotherapy (NAC) group. The concordance varied greatly in subset analysis with respect to TNM stage and molecular subtype. AC recommendations were concordant in 92.3% of stage III breast cancer and 50.8% of stage I. However, the concordance varied by molecular subtype, which was higher for triple negative breast cancer (89.3%) than others. The chemotherapy regimen concordance declined significantly with increasing age, except for the age group 41–50 years.

Conclusions: Chemotherapy regimens provided by WFO did not exhibit a high degree of agreement with those suggested by oncologists in clinical practice in the hospital in China. The current effort is underway to enhance WFO’s capabilities as a cognitive decision support tool by incorporating regional guidelines, enabling oncologists and patients to benefit from WFO worldwide.

Keywords: Watson for Oncology (WFO); breast cancer; chemotherapy; concordance


Submitted Sep 08, 2018. Accepted for publication Jan 04, 2019.

doi: 10.21037/tcr.2019.01.34


Introduction

Breast cancer is the most common cancer and the leading cause of cancer death among women worldwide (1). The widespread use of adjuvant systemic therapies, including chemotherapy, endocrine therapy, and anti-HER2 therapy, has contributed significantly to improving breast cancer outcomes (2-5).

Chemotherapy plays an important role in breast cancer systemic treatments. It was initially prescribed to patients using an adjuvant alkylating agent, based on the first randomized trial NSABP B-01 reported in 1968 (6). In contrast with surgery that evolved from more aggressive to less aggressive, chemotherapy regimens and their indications expanded (7). Adjuvant cytotoxic chemotherapy regimens have evolved from single alkylating agents to polychemotherapy regimens incorporating anthracyclines and/or taxanes. The widespread adoption of more effective chemotherapy regimens contributed to declining breast cancer mortality globally, however, it also resulted in many patients being unintentionally over-treated with chemotherapy who might be cured without chemotherapy (8,9). Nowadays, women with early-stage breast cancer are faced with challenging chemotherapy regimen decisions. Identifying which patients derive greatest benefit from chemotherapy and which regimen is best for them have been being discussed over the past decades (9,10).

Along with the growth of massive genetic and clinical databases, breast cancer treatment developed quickly, the cycle time for changes to breast cancer treatment guidelines was shorter and shorter. Currently, predictive factors that identify benefit from chemotherapy include classical clinicopathologic characteristics (tumor size and number of positive axillary lymph nodes), and expression of estrogen receptor (ER), progesterone receptor (PR), HER2 and Ki-67, as well as multiparameter gene expression assays (11-14). Maybe some other more effective predictive factors will be identified to realize fully the promise of precision chemotherapy in the near future. Oncologists who treat breast cancer are challenged by a large and rapidly expanding knowledge base. There is always little time available for oncologists to track and access relevant information using in the clinical practice (15). We have anticipated that an oncologist equipped with a computer-based decision support system will be able to select for any given patient an optimal regimen that maximizes therapeutic efficacy while minimizing the side effects correlating with ineffective treatments.

IBM Watson for Oncology (WFO) is an artificial intelligence cognitive computing system that provides confidence-ranked, evidence-based treatment recommendations for cancer. It was developed in collaboration with cancer experts at Memorial Sloan Kettering Cancer Center (MSKCC). The system provides oncologists with treatment options, which are derived from established guidelines, medical literature, and training from patient cases. A retrospective, observational study carried out in India showed that treatment decision made by WFO exhibited a high degree of agreement with those of the multidisciplinary tumor board (16). Based on their study, non-concordance may contribute to the demographic characteristics, such as comorbidity burden, patients’ preferences, and level of social support systems, as well as different treatment guidelines.

In the present study, we examine the level of agreement for primary breast cancer chemotherapy [including adjuvant chemotherapy (AC) and neoadjuvant chemotherapy (NAC)] between WFO recommended and clinical use from The First Affiliated Hospital with Nanjing Medical University (Nanjing, China) in a large population of breast cancer cases. The study was aim to determine the chemotherapy concordance, and discuss the potential reasons of non-concordance.


Methods

Patients and study design

This retrospective, single-center, non-interventional study reviewed 1,301 breast cancer patients in Jiangsu Province Hospital with Nanjing Medical University, China from June 2013 to December 2017. The eligible patients were female, ≥20 years old with stage I to III invasive breast cancer, who received chemotherapy determined according to established clinical risk factors and breast cancer guidelines. Patients were excluded if they were male, had stage IV breast cancer, or relapsed after primary therapy. All the entered patients were separated into two groups: AC group included 1,121 patients who received AC after surgery, and NAC group included 180 patients who received NAC after diagnosis by biopsy. Oncologists determined all the chemotherapy regimens used in clinic. Three trained senior oncology fellows reviewed the electronic medical record system, and patients’ clinical information and recommended treatment regimens between 2013 and 2017 were recorded. The design of the study is shown in Figure 1.

Figure 1 The flow diagram of the study. WFO, Watson for Oncology.

The study protocol was approved by the ethics committee of The First Affiliated Hospital with Nanjing Medical University (2018-SR-368) and was conducted in accordance with the Helsinki Declaration of 1964 (revised 2008). Due to the retrospective nature of this study, the need for informed consent was waived.

Pathologic assessment

In the present study, patients diagnosed with metastasis by imaging examination were all excluded from our study. For patients in the AC group, pathological tumor size and axillary lymph node status were assessed after surgery, to determine pathologic TNM stage according to the American Joint Committee on Cancer (AJCC). For patients in the NAC group, clinical tumor size and clinical axillary lymph node status were assessed at diagnosis, to determine clinical TNM stage. Additionally, ER, PR, HER2 status, and Ki-67 were assessed from the biopsies taken at diagnosis or tumor tissues taken at surgery, to allocate tumors in molecular subtype classification, as suggested by the St Gallen 2017 consensus. The following classifications were used:

Luminal A: ER positive and PR positive (cut-point ≥20%), HER2 negative, Ki-67 <14%.

Luminal B/HER2 negative: ER positive and HER2 negative, and at least one of: Ki-67 ≥14%, PR negative or low (cut-point <20%).

Luminal B/HER2 positive: ER positive over-expressed or amplified, any PR, and any Ki-67.

HER2 positive: HER2 over-expressed or amplified, ER and PR absent.

TN (triple negative): ER and PR absent, and HER2 negative.

WFO and concordance determination

IBM WFO developed in collaboration with MSKCC, which is a cognitive computing system able to extract structured data from free text documents using natural language processing (NLP). It is a technology platform that uses NLP and machine learning to reveal insights from large amounts of unstructured data. It includes text from more than 300 medical journals and textbooks, MSKCC treatment guideline, and literature hand-selected by MSK experts.

Patients’ data, including patient characteristics, tumor characteristics and stage, and some laboratory finding, were abstracted from electronic medical record system and entered manually into WFO by the trained senior oncology fellows.

After processing, chemotherapy recommendations were provided in 3 categories, green represents chemotherapy regimens “Recommended” with a strong base of evidence; amber represents chemotherapy regimens “For Consideration” which oncologists may consider as suitable alternatives base on their clinical judgment; and red represents chemotherapy regimens “Not Recommended”, due to strong evidence against their use or some specific contraindications. Concordance was analyzed by comparing the decisions made by the oncologists to those proposed by WFO. Concordance was achieved when oncologists’ treatment suggestions were in the “Recommended” or “For Consideration” categories given by WFO. WFO and the physicians who ran the cases were blinded to the chemotherapy regimens determined by oncologists.

Data analysis and statistics

The primary study objective was to evaluate the concordance between chemotherapy regimens oncologists’ suggested and WFO proposed. Descriptive statistics of breast cancer case characteristics were presented as means ± standard deviation or median (range). Categorical variables were expressed as percentage (%). The concordance was expressed as percent agreement. Controlling for cancer characteristics, including patient age, menopausal status, tumor TNM stage, and molecular subtype, a logistic regression model of concordance between WFO and oncologists’ suggestions was estimated with odds ratios (ORs) and 95% confidence intervals (CIs).

All statistical analyses were performed using Stata version 11.0 (StataCorp, College Station, TX, USA), and a significant difference was concluded for P<0.05.


Results

Baseline characteristics

A total of 1,301 female patients diagnosed with stage I to III breast cancer between June 2013 and December 2017 were enrolled in this retrospective study. The clinicopathological characteristics of the total sample of breast cancer patients who received AC after surgery from June 2013 to December 2017 are reported in Table 1. The mean age at the time of chemotherapy started was 51.1 years. Of the 1,121 patients, pathological TNM stage and molecular subtype varied slightly, with more patients having stage II tumors (46.3%), and more patients having Luminal B (HER2 negative) tumors (52.1%).

Table 1

Characteristics of breast cancer cases receiving adjuvant chemotherapy after primary surgery

Variable Number
Female, n (%) 1,121 [100]
Age, mean ± SD, years 51.1±11.1
Menopausal status, n (%)
   Pre-menopausal 577 (51.47)
   Post-menopausal 544 (48.53)
Tumor location, n (%)
   Left 572 (51.03)
   Right 549 (48.97)
Surgery date (year), n (%)
   ~2014 138 (12.31)
   2015 368 (32.83)
   2016 416 (37.11)
   2017 199 (17.75)
Surgery type, n (%)
   Surgery for primary site
      Conserving surgery 247 (22.03)
      Mastectomy 874 (77.97)
          Without plastic surgery 833 (74.31)
          With plastic surgery 41 (3.66)
   Surgery for axillary lymph node
      SLNB 449 (40.05)
      ALND 567 (50.58)
      SLNB + ALND 105 (9.37)
Histopathology, n (%)
   IDC 1,060 (94.56)
   ILC 30 (2.68)
   Other 31 (2.77)
Pathological T stage, n (%)
   pT1 562 (50.13)
   pT2 528 (47.10)
   pT3 31 (2.77)
Pathological N stage, n (%)
   pN0 663 (59.14)
   pN1 254 (22.66)
   pN2 120 (10.70)
   pN3 84 (7.49)
Pathological TNM stage, n (%)I
   I 394 (35.15)
   II 519 (46.30)
   III 208 (18.55)
ER status, n (%)
   Positive 307 (27.39)
   Negative 814 (72.61)
PR status, n (%)
   Positive 718 (64.05)
   Negative 403 (35.95)
HER2 status, n (%)
   Positive 293 (26.14)
   Negative 828 (73.86)
Ki-67, n (%)
   <14% 119 (10.62)
   14–50% 617 (55.04)
   >50% 385 (34.34)
Molecular subtype, n (%)
   Luminal A 85 (7.58)
   Luminal B/HER2 negative 584 (52.10)
   Luminal B/HER2 positive 162 (14.45)
   HER2 positive 131 (11.69)
   Triple negative 159 (14.18)
Vessel invasive status, n (%)
   Yes 218 (19.45)
   No 903 (80.55)

SLNB, sentinel lymph node biopsy; ALND, axillary lymph node dissection; ILC, invasive lobular carcinoma; IDC, invasive ductal carcinoma; ER, estrogen receptor; PR, progesterone receptor.

Table 2 shows the characteristics of 180 breast cancer patients who received NAC after biopsy from January 2014 to October 2017. The mean age at the time of NAC was 48.2 years. Similar to patients in the AC group, more patients presented with Luminal B (HER2 negative) tumors (39.4%) and stage II tumors (87.8%) in this group.

Table 2

Characteristics of breast cancer cases received neoadjuvant chemotherapy after diagnosis

Variable Number
Female, n (%) 180 [100]
Age, mean ± SD, years 48.2±11.0
Menopausal status
   Pre-menopausal 102 (56.67)
   Post-menopausal 78 (43.33)
Tumor location
   Left 94 (52.22)
   Right 86 (47.78)
Biopsy date (year), n (%)
   ~2014 23 (12.78)
   2015 43 (23.89)
   2016 79 (43.89)
   2017 35 (19.44)
Histopathology, n (%)
   Invasive breast cancer 180 [100]
Clinical T stage, n (%)
   cT1 21 (11.67)
   cT2 139 (77.22)
   cT3 20 (11.11)
Clinical N stage, n (%)
   cN0 67 (37.22)
   cN1 106 (58.89)
   cN2 7 (3.89)
Clinical TNM stage, n (%)
   I
   II 158 (87.78)
   III 22 (12.22)
Biopsy ER status, n (%)
   Positive 120 (66.67)
   Negative 60 (33.33)
Biopsy PR status, n (%)
   Positive 96 (53.33)
   Negative 84 (46.67)
Biopsy HER2 status, n (%)
   Positive 72 (40.00)
   Negative 108 (60.00)
Biopsy Ki-67, n (%)
   <14% 9 (5.00)
   14–50% 130 (72.22)
   >50% 41 (22.78)
Biopsy molecular subtype, n (%)
   Luminal A 8 (4.44)
   Luminal B/HER2 negative 71 (39.44)
   Luminal B/HER2 positive 41 (22.78)
   HER2 positive 31 (17.22)
   Triple negative 29 (16.11)

ER, estrogen receptor; PR, progesterone receptor.

Concordance analysis

Overall chemotherapy regimen concordance was 69.4%, with 65.0% in AC group and 96.7% in NAC group (Table 3). In subset analysis of breast cancer with respect to TNM stage and molecular subtype, the concordance varied greatly. AC recommendations were concordant in 92.3% of stage III breast cancer and 50.8% of stage I breast cancer. Moreover, the concordance varied by molecular subtype, which was higher for triple negative breast cancer (89.3%) than Luminal A and Luminal B/HER2 negative breast cancer (55.3% and 52.7%, respectively) (Table 3, Figure 2). Patients’ age also played a vital role in chemotherapy concordance rate. The chemotherapy regimen concordance declined significantly with increasing age, except for the age group 41–50 years (Table 3, Figure 3). As for chemotherapy regimen in NAC group, subset analyses of treatment concordance by stage and molecular subtype were also carried out. The regimen concordances were high in all the subgroups, which narrowly ranged from 93.1% to 100% (Table 3, Figure 2).

Table 3

Clinical use and WFO recommendations

Review of breast cancer cases Concordant cases, n (%)
Recommended For consideration Total
Total (n=1,301) 327 (25.13) 576 (44.27) 903 (69.41)
Adjuvant chemotherapy (n=1,121) 220 (19.63) 509 (45.41) 729 (65.03)
   Surgery date, year
      ~2014 (n=138) 35 (25.36) 51 (36.96) 86 (62.32)
      2015 (n=368) 71 (19.29) 169 (45.92) 240 (65.22)
      2016 (n=416) 79 (18.99) 197 (47.36) 276 (66.35)
      2017 (n=199) 35 (17.59) 92 (46.23) 127 (63.82)
   Age, years
      ≤40 (n=189) 42 (22.22) 90 (47.62) 132 (69.84)
      41–50 (n=392) 75 (19.13) 204 (52.04) 279 (71.17)
      51–60 (n=313) 60 (19.17) 143 (45.69) 203 (64.86)
      61–70 (n=170) 31 (18.24) 59 (34.71) 90 (52.94)
      ≥71 (n=57) 12 (21.05) 13 (22.81) 25 (43.86)
   Pathologic TNM stage
      I (n=394) 43 (10.91) 157 (39.85) 200 (50.76)
      II (n=519) 109 (21.00) 228 (43.93) 337 (64.93)
      III (n=208) 68 (32.69) 124 (59.62) 192 (92.31)
   Molecular subtype
      Luminal A (n=85) 17 (20.00) 30 (35.29) 47 (55.29)
      Luminal B/HER2 negative (n=584) 92 (15.75) 216 (36.99) 308 (52.74)
      Luminal B/HER2 positive (n=162) 41 (25.31) 89 (54.94) 130 (80.25)
      HER2 positive (n=131) 32 (24.43) 70 (53.44) 102 (77.86)
      Triple negative (n=159) 38 (23.90) 104 (65.41) 142 (89.31)
Neoadjuvant chemotherapy (n=180) 107 (59.44) 67 (37.22) 174 (96.67)
   Biopsy date, year
      ~2014 (n=23) 16 (69.57) 5 (21.74) 21 (91.30)
      2015 (n=43) 34 (79.07) 9 (20.93) 43 (100.00)
      2016 (n=79) 44 (55.70) 33 (41.77) 77 (97.47)
      2017 (n=35) 13 (37.14) 20 (57.14) 33 (94.29)
   Clinical TNM stage
      II (n=158) 93 (58.86) 60 (37.97) 153 (96.84)
      III (n=22) 14 (63.64) 7 (31.82) 21 (95.45)
   Molecular subtype
      Luminal A (n=8) 6 (75.00) 2 (25.00) 8 (100.00)
      Luminal B/HER2 negative (n=71) 39 (54.93) 31 (43.66) 70 (98.59)
      Luminal B/HER2 positive (n=41) 27 (65.85) 12 (29.27) 39 (95.12)
      HER2 positive (n=31) 15 (48.39) 15 (48.39) 30 (96.77)
      Triple negative (n=29) 20 (68.97) 7 (24.14) 27 (93.10)

WFO, Watson for Oncology.

Figure 2 Chemotherapy regimen concordance between WFO and Clinical use by breast cancer stage and molecular subtype in AC group (A,B) and NAC group (C,D). WFO, Watson for Oncology; AC, adjuvant chemotherapy; NAC, neoadjuvant chemotherapy therapy; A, Luminal A; B1, Luminal B/HER2 negative; B2, Luminal B/HER2 positive; H, HER2 positive; T, triple-negative.
Figure 3 Chemotherapy regimen concordance between WFO and clinical use by age in AC group. AC, adjuvant chemotherapy; WFO, Watson for Oncology.

Results from logistic regression of concordance are presented in Table 4. ORs were analyzed by patient age, menopausal status, TNM stage, Molecular subtype, Ki-67 status, and vessel invasive status. In univariate analysis, old age and postmenopausal were associated significantly lower concordance rates. High TNM stage, high Ki-67 expression (Ki-67 >50%), and invasive vessel were demonstrated to increase the concordance (all P<0.05). ORs of concordance by molecular subtype, showed that compared with Luminal A cancers, Luminal B/HER2 positive, HER2 positive, and triple negative cancers were significantly more likely to be concordant (all P<0.05).

Table 4

Logistic regression model of concordance between WFO and clinical use for patients receiving adjuvant chemotherapy after surgery (N=1,301)

Variable Univariate Cox regression Multivariable Cox regression
Odds ratio (95% CI) P value Adjusted odds ratio (95% CI) P value
Age at diagnosis, years
   ≤40 (reference) 1.00 1.00
   41–50 1.07 (0.73–1.56) 0.741 1.10 (0.72–1.69) 0.665
   51–60 0.80 (0.54–1.17) 0.251 0.99 (0.54–1.81) 0.964
   61–70 0.49 (0.32–0.75) 0.001 0.61 (0.31–1.21) 0.159
   70+ 0.34 (0.18–0.629) <0.001 0.33 (0.14–0.78) 0.012
Menopausal status
   Premenopausal (reference) 1.00 1.00
   Postmenopausal 0.61 (0.47–0.78) <0.001 0.69 (0.41–1.13) 0.140
Pathological TNM stage
   I (reference) 1.00 1.00
   II 1.80 (1.37–2.35) <0.001 2.12 (1.57–2.88) <0.001
   III 11.64 (6.74–20.11) <0.001 13.87 (7.66–25.11) <0.001
Ki-67
   <14% (reference) 1.00 1.00
   14–50% 1.28 (0.86–1.90) 0.222 1.44 (0.69–3.02) 0.329
   >50% 2.86 (1.86–4.40) <0.001 1.75 (0.81–3.75) 0.154
Molecular subtype
   Luminal A (reference) 1.00 1.00
   Luminal B/HER2 negative 0.90 (0.57–1.43) 0.659 0.54 (0.23–1.26) 0.153
   Luminal B/HER2 positive 3.28 (1.85–5.85) <0.001 1.77 (0.70–4.51) 0.23
   HER2 positive 2.84 (1.57–5.15) 0.001 1.80 (0.70–4.60) 0.223
   Triple negative 6.75 (3.49–13.07) <0.001 5.95 (2.25–15.75) <0.001
Vessel invasive status
   No (reference) 1.00 1.00
   Yes 2.32 (1.63–3.30) <0.001 1.44 (0.954–2.17) 0.082

Potential confounders: age, menopausal status, TNM stage, molecular subtype, Ki-67 status, and vessel invasive status. WFO, Watson for Oncology.

Adjusted for potential confounders in multivariate analysis, concordance was only significantly lower for patients 70 years older, compared with patients 40 years of age and younger (OR =0.33, 95% CI, 0.14–0.78, P=0.012). Stage II and III diseases were still significantly more likely to concordant than stage I disease (all P<0.05). Additionally, multivariate analysis revealed that only triple-negative breast cancers were significantly more likely to be concordant than Luminal A (P<0.001).

Disagreements in AC population

Table 5 presents the distribution of TNM stage and molecular subtype of non-concordant cases according to different AC regimen used in clinic. First, we analyzed the 245 patients who received chemotherapy without HER2 target therapy. Of the 245 patients, 41 patients received AC (doxorubicin and cyclophosphamide) chemotherapy, 106 patients received TC (docetaxel and cyclophosphamide), 30 patients received FEC (fluorouracil, epirubicin and cyclophosphamide), 36 patients received FEC-T (3 cycles of FEC followed by 3 cycles of docetaxel), and 32 patients received AC-T (4 cycles of AC followed by 4 cycles of paclitaxel) as oncologists suggested in clinic, while WFO recommended CMF (cyclophosphamide, methotrexate, and fluorouracil), ddAC-T (dose-dense AC-T), or no chemotherapy. It is obvious that most of the patients were Luminal A or Luminal B/HER2 negative irrespective of tumor stage, except for a small number of patients with HER2 positive or triple negative but stage I cancer.

Table 5

Characteristics of non-concordant cases according to different chemotherapy regimens used in clinic

Clinical chemotherapy regimen WFO chemotherapy regimen Molecular subtype TNM stage
I II III
AC [41] CMF/ddAC-T/none A 3 3
B1 23 10 1
H 1 (0.2 cm)
AC-T [32] CMF/ddAC-T/none B1 17 9
T 6
TC [106] CMF/ddAC-T/none A 1 4 1
B1 27 60 4
H 1 (0.1 cm)
T 7 (0.4–1.8 cm) 1 (76 y)
FEC [30] CMF/ddAC-T B1 14 16
FEC-T [36] CMF/ddAC-T B1 11 22
T 2 1
AC-TH [10] TH [1]/none B2 3 (0.2–0.7 cm)
H 7 (0.1–0.5 cm)
FEC-TH [17] TH/ddAC-TH/none B2 5 (0.5–1.8 cm) 7
H 2 (0.2–0.3 cm) 3
TCH [26] ddAC-TH/TH B2 6 (0.2–1.8 cm) 10
H 4 5 1
PH [5] ddAC-TH/none B2 1
H 3 (0.1–0.3 cm) 1 (70 y)
None [89] CMF/ddAC-T A 17 9
B1 33 23 6 (60+ y)
H 1

WFO, Watson for Oncology; AC, doxorubicin and cyclophosphamide; AC-T, 4 cycles of AC followed by 4 cycles of paclitaxel; TC, docetaxel and cyclophosphamide; FEC, fluorouracil, epirubicin and cyclophosphamide; FEC-T, 3 cycles of FEC followed by 3 cycles of docetaxel; AC-TH, AC-T plus trastuzumab; FEC-TH, FEC-T plus trastuzumab; TCH, docetaxel and carboplatin plus trastuzumab; PH, weekly paclitaxel and trastuzumab for 12 weeks; CMF, cyclophosphamide, methotrexate, and fluorouracil; ddAC-T, dose-dense AC-T.

For Luminal B/HER2 positive and HER2 positive breast cancers, 10 patients received AC-TH (AC-T plus trastuzumab) chemotherapy, 17 patients received FEC-TH (FEC-T plus trastuzumab), 26 patients received TCH (docetaxel and carboplatin plus trastuzumab), and 5 patients received PH (weekly paclitaxel and trastuzumab for 12 weeks), different from WFO recommended. Among these 58 patients, 31 (53.4%) patients were stage I, 26 (44.8%) patients were stage II, and only 1 (0.2%) patient was stage III.

It is worth to note that a total of 89 patients did not receive chemotherapy in clinic, and all of them were Luminal A and Luminal B1, except for one patient with HER2 positive who rejected chemotherapy treatment.


Discussion

This large population based retrospective, observational study shows that chemotherapy regimen options suggested by WFO were concordant with the therapeutic decisions by oncologists (clinical use) in the large majority of breast cancer patients treated with NAC before surgery. The degrees of concordance in patients treated with AC was much lower, reflecting the differences in practice patterns between the United States, (where WFO was trained) and The First Affiliated Hospital with Nanjing Medical University in China. In subgroup analysis, there were still higher degrees of concordance between WFO treatments options and the oncologists’ decision among stage III, HER2 positive, and triple negative breast cancers. However, with respect to Luminal A and Luminal B/HER2 negative disease, lots of improvements are needed from WFO.

We speculated that potential reasons for non-concordance included: (I) local medications or medication combinations not available in WFO; (II) differences in criteria for use of certain chemotherapy regimen; (III) oncologist preference; (IV) patient and family preference; (V) Ki-67 is an important factor in determining molecular subtype, which is not considered in WFO. We will discuss the non-concordant regimen in details below.

In 1976, the efficacy of CMF was first reported, as adjuvant treatment for node positive breast cancer (17). Its long-term results represent an important step in the contemporary evolution of breast cancer treatment. And then CMF has been expanded to patients with node negative cancer (18). As recommended by WFO, a majority of cases were suggested to receive CMF chemotherapy. However, CMF has not been used for years in our hospital, or in most of cities in China.

Doxorubicin was first evaluated in NSABP B-11 trial (19). Later in 1990, NSABP B-15 trial was carried out in 2,194 patients with node-positive disease to AC every 3 weeks for 4 cycles versus CMF for 6 cycles, which demonstrated similar 3-year DFS rates and OS rates (20). Subsequently, NSABP B-23 also found no difference in outcomes in patients with node-negative disease who were treated with AC or CMF (21). Additionally, results from the US Oncology Research phase III trial demonstrated that TC was associated with significantly improved outcome compared with AC (22). As Table 5 presents, when WFO recommended CMF, oncologists chose AC or TC for some cases in our study. AC and TC are two common chemotherapy regimens in our clinic practice when the disease is in early stage or is a Luminal type in low risk.

The two trials, FASG 2 and 7 found that there was a trend in favor of FEC for OS compared with tamoxifen alone (23). The EBCTCG meta-analysis in 2012 found that FEC was more effective in reducing breast cancer mortality compared to CMF (RR =0.78, P=0.0004) (2). In addition, the PACS01 trial evaluated FEC with FEC-T, which found that FEC-T was associated with improved DFS (HR =0.85, P=0.036) and OS (HR =0.75, P=0.007) (24). FEC and FEC-T were two common regimens used before the year 2017 in our hospital, but never recommended by WFO.

CALGB 9344 (25) and NSABP B-28 (26) both demonstrated AC-T was associated with better outcome than AC. Afterwards, results of C9741 after a median 6.5 years of follow-up favored ddAC-T in DFS and OS in ER-negative disease but not ER-positive disease (27). AC-T and ddAC-T are two favorite regimens in WFO, which we always prefer for patients in high risk, including patients with young age, large tumor size, positive lymph node, and Triple-negative subtype.

If HER2 is positive, trastuzumab will be added to the regimens, like FEC-TH, AC-TH and ddAC-TH. These are common-use regimens in clinical practice. The results of BCIRG-006 trial showed that risk-benefit ration favored the non-anthracycline TCH regimen over AC-TH, given its similar efficacy and fewer toxic effects (28). So, for some cases that WFO recommend ddAC-TH, the oncologists preferred TCH instead, which is not included in WFO. Additionally, PH is another choice for oncologists in clinical practice. An uncontrolled, single-group study in 406 patients resulted that patients with predominantly stage I, HER2 positive, and node negative breast cancer, treatment with PH correlated with a risk of early recurrence of about 2% (29). According to the evidence above, oncologists usually chose the PH regimen for stage I and HER2 positive patients.

Notably, there were 89 patients who did not receive any chemotherapy. Nearly all the patients were Luminal A or Luminal B1. These are endocrine responsive breast cancers, and most of them would get no significant beneficial effect from chemotherapy.

Several limitations of this study should be considered. First, the present study was a retrospective, observational study without any controls. And we cannot compare the efficacy of regimens suggested by oncologists and WFO recommendations. Therefore, lack of concordance does not necessarily provide evidence regarding whether the clinical regimen or WFO was “correct” in its recommendation. Second, it is better to assess the Oncotype DX Recurrence Score to identify which group of the patients are in high risk and would benefit from chemotherapy, especially for Luminal A and Luminal B/HER2 negative disease. No multigene assay was used in making clinical decisions in our study. Third, reasons for non-concordance such as insurance requirements, cost, and patient and oncologist preferences were not analyzed in our study.


Conclusions

WFO is a step towards personalized medicine. It could be an essential tool to oncologists by reducing the cognitive burden of physicians in keeping up with medical literature by providing clinically actionable insights to assist them in treating patients. Chemotherapy regimens provided by WFO did not exhibit a high degree of agreement with those suggested by oncologists in clinical practice in the hospital in China. We supposed that WFO’s capabilities as a cognitive decision support can be further improved by an incorporating regional guideline, enabling oncologists and patients to benefit from WFO worldwide. However, it should be kept in mind that WFO will be only an assisting tool and it will never be able to replace the patient-doctor relationship, which is a very essential component in treating patients suffering with cancer.


Acknowledgments

Funding: This work was supported by the National Natural Science Foundation of China [81502286, 81502299, 81572607 and 81771953], the 2016 Industry Prospecting and Common Key Technology Key Projects of Jiangsu Province Science and Technology Department [BE2016002-4], the 2016 projects of Nanjing Science Bureau [201608003], and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).


Footnote

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tcr.2019.01.34). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol was approved by the ethics committee of The First Affiliated Hospital with Nanjing Medical University (2018-SR-368) and was conducted in accordance with the Helsinki Declaration of 1964 (as revised in 2008). Due to the retrospective nature of this study, the need for informed consent was waived.

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


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Cite this article as: Pan H, Tao J, Qian M, Zhou W, Qian Y, Xie H, Jing S, Xu T, Zhang X, Dai Z, You M, Liu Y, Liu X, Wang S. Concordance assessment of Watson for Oncology in breast cancer chemotherapy: first China experience. Transl Cancer Res 2019;8(2):389-401. doi: 10.21037/tcr.2019.01.34

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