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  Table of Contents  
Year : 2017  |  Volume : 54  |  Issue : 1  |  Page : 352-357

Predicting loco-regional recurrence risk in T1, T2 breast cancer with 1–3 positive axillary nodes postmastectomy: Development of a predictive nomogram

1 Department of Radiation Oncology, Tata Memorial Centre, Mumbai, Maharashtra, India
2 Department of Medical Statistics, Tata Memorial Centre, Mumbai, Maharashtra, India
3 Department of Surgical Oncology, Tata Memorial Centre, Mumbai, Maharashtra, India
4 Department of Pathology, Tata Memorial Centre, Mumbai, Maharashtra, India
5 Department of Medical Oncology, Tata Memorial Centre, Mumbai, Maharashtra, India

Date of Web Publication1-Dec-2017

Correspondence Address:
Dr. R Sarin
Department of Radiation Oncology, Tata Memorial Centre, Mumbai, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijc.IJC_178_17

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 » Abstract 

BACKGROUND: Role of postmastectomy radiotherapy (PMRT) in early breast cancer with 1–3 positive axillary nodes is still controversial. Hence, there is a need to identify subgroup of patients who have sufficiently high risk of disease recurrence to benefit from PMRT. AIM: The aim is to evaluate clinical outcomes of patients postmastectomy having pathological T1–T2 tumors with 1–3 positive axillary lymph nodes (LNs) treated with adjuvant systemic therapy and develop a predictive nomogram. MATERIALS AND METHODS: Data collected retrospectively from eligible patients from 2005 to 2011. Kaplan–Meier survival analysis was used for all time-to-event analysis. Various known clinical and pathological risk factors were correlated with outcome using uni- and multi-variable analysis in SPSS version 21. All comparisons were two-tailed and P < 0.05 were considered statistically significant. The nomogram to predict the risk of loco-regional control (LRC) was developed using least absolute shrinkage and selection operator shrinkage model in software. RESULTS: 38/242 (15.7%) patients had recurrent disease at loco-regional (10 patients), distant sites (22 patients) and simultaneous loco-regional and distant sites (6 patients) at a median follow-up 59.5 (range 4–133) months. Five years estimate of LRC, distant disease-free survival (DFS), DFS, cause-specific survival and overall survival was 87.8%, 85.4%, 84.2%, 93.1%, and 91.5%, respectively. Pathological tumor size, margin status, LN ratio as continuous variables and grade and triple negative breast cancer status as categorical variables were the risk factors included in the model for building nomogram. CONCLUSION: The nomogram developed based on institutional data can be a valuable tool in guiding adjuvant PMRT depending on the risk of 5 years loco-regional recurrence.

Keywords: Early breast cancer, nomogram, postmastectomy radiotherapy, recurrence risk

How to cite this article:
Wadasadawala T, Kannan S, Gudi S, Rishi A, Budrukkar A, Parmar V, Shet T, Desai S, Gupta S, Badwe R, Sarin R. Predicting loco-regional recurrence risk in T1, T2 breast cancer with 1–3 positive axillary nodes postmastectomy: Development of a predictive nomogram. Indian J Cancer 2017;54:352-7

How to cite this URL:
Wadasadawala T, Kannan S, Gudi S, Rishi A, Budrukkar A, Parmar V, Shet T, Desai S, Gupta S, Badwe R, Sarin R. Predicting loco-regional recurrence risk in T1, T2 breast cancer with 1–3 positive axillary nodes postmastectomy: Development of a predictive nomogram. Indian J Cancer [serial online] 2017 [cited 2020 Mar 31];54:352-7. Available from:

 » Introduction Top

Breast cancer has been a heterogeneous disease with diverse clinical behavior depending on patient demographics, disease biology, and therapeutic interventions. This entails definite need for tailored therapy to maximize disease control without increase in the treatment related toxicity. Patients with early breast cancer (EBC) treated with modified radical mastectomy (MRM) require postmastectomy radiotherapy (PMRT) if there are high-risk histopathological features based on evidence from three large randomized trials and meta-analyses from the EBC trialist's collaborative group (EBCTCG).[1],[2],[3] Indexed medical literature and international consensus guidelines support the role of PMRT in patients with large tumors (>5 cm) or multiple (4 or more) positive axillary lymph nodes (LNs).[4],[5] PMRT has shown to improve loco-regional disease control as well as overall survival (OS) in such patients. Considerable controversy exists regarding the role of PMRT in small tumors (pathological size <5 cm) with one to three positive axillary nodes and no randomized trials to answer this question have been published till date. These guidelines also recommend against the use of PMRT in patients with small tumors (pathological size <5 cm) with negative axillary nodes.

A randomized trial (MA 25) initiated to answer this question was terminated due to poor accrual and another multicentric, randomized study (SUPREMO) has completed accrual and the results are awaited. However, multiple nonrandomized studies have identified high-risk features in this subgroup of patients to define the role of PMRT. A recently published meta-analysis by the EBCTCG which looked at the role of PMRT in such patients showed the benefit of radiotherapy in this subgroup of patients.[6] This meta-analysis was based on studies conducted in early era and the treatment methods (including surgical technique, chemotherapy regimens, and radiotherapy techniques) used in these studies differ significantly from the current treatment standards. Due to the establishment of effective systemic therapies in the breast cancer treatment algorithm, even for small tumors, the risk of loco-regional relapse has reduced considerably. Although some recent guidelines strongly recommend PMRT for this group of patients, we think it is inappropriate to consider this group as a homogenous group and consider PMRT to all patients.[7] There is a definite need to identify a subgroup of patients who actually benefit PMRT. As the role of PMRT is still debatable for one to three positive nodes, we aimed to identify subgroups with high risk of recurrence in this patient cohort based on our institutional data and to develop a nomogram based on continuous risk estimation modeling, to predict the probability of loco-regional recurrence (LRR) at 5 and 7 years in women with EBC postmastectomy.

 » Materials And Methods Top


Two hundred and forty-two patients with EBC treated with MRM at our institution between the years 2005 and 2011 and had <5 cm tumor size with one to three positive axillary nodes on histopathological evaluation were considered eligible. Patients with recurrent, bilateral, or higher disease burden (T3–T4) were excluded from the study. Data were collected from clinical case records, electronic medical records as well as telephonic follow up. Ethical clearance for conducting this retrospective study was obtained from the Institutional Ethics Committee (IEC) which granted a consent waiver for reviewing the medical records of the patients. The waiver for consent was granted by the IEC as the study involved not more than minimal risk and involved retrospective analysis of the data available in the clinical records as part of routine care.

Adjuvant therapy

Majority of patients received anthracycline (61%) and/or taxane-based (36%) chemotherapy regimens as per the prevailing institutional protocol. Other regimens (cyclophosphamide, methotrexate, 5-fluorouracil) were used in 3% of the patients. Adjuvant hormone therapy was advised for all hormone receptor positive women. Patients who received adjuvant radiotherapy were excluded. Women were followed every 6 months up to 5 years and annually thereafter. Patient characteristics are depicted in [Table 1].
Table 1: Patient characteristics

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Statistical methods

Statistical analysis of the extracted data was performed using Statistical Package for Social Sciences (SPSS, Chicago, IL, USA) software version 21. Kaplan–Meier (KM) curves were used to generate actuarial time-to-event curves for loco-regional control (LRC), distant disease-free survival (D-DFS), DFS, cause-specific survival (CSS) and OS. Disease-free interval was calculated from the date of diagnosis to the date of any recurrence or last follow-up or death. Events considered for each endpoint for statistical analysis are in accordance with the DATECAN guidelines for breast cancer trials. Thus, events used for LRR included recurrence at local, regional (ipsilateral supraclavicular, axillary, or internal mammary LNs) or both sites (with or without distant metastases) and death due to disease or any cause.[8] The primary objective of the analysis and building of nomogram was to select patients at sufficient high risk for loco-regional relapse so as to merit adjuvant radiotherapy. For univariable analysis, the effect of each potential clinico-pathological risk factor on LRC was tested for statistical significance using the log-rank test. All comparisons were two-tailed and P < 0.05 were considered to be statistically significant. Multivariable analysis was carried using Cox regression analysis, and all risk factors with P < 0.25 were analyzed using enter method.[9] These variables were then used for nomogram development to predict the risk of LRC in package web application.[10] Least absolute shrinkage and selection operator (LASSO) shrinkage model was used for the development of nomogram as it is considered a reasonable option for use under the constraint of few events per variable. The internal validation of the predictive values obtained from the nomogram for LRC was tested using the area under the curve (AUC) with 200 bootstrap samples to prevent over-fitting and to obtain an unbiased estimate. AUC is an appropriate measure for ordinary continuous outcomes, dichotomous variables as well as censored time-event response variables an AUC of 1.0 indicates perfect predictive ability, whereas 0.5 represents no predictive discrimination. Calibration of the nomogram was assessed by plotting observed survival outcomes (mean KM estimates) against the 5 and 7 years predicted LRC probabilities at the same time point by splitting the data into quartiles.

 » Results Top

Univariable and multivariable analysis

At a median follow-up of 59.5 (range 4–133) months, the 5 years estimate of LRC, D-DFS, DFS, CSS and OS was 87.8%, 85.4%, 84.2%, 93.1%, and 91.5%, respectively. A total of 38 (15.7%) patients had recurrent disease. Loco-regional only recurrence occurred in 10 patients (4.1%), distant only recurrence in 22 patients (9.1%) and simultaneous loco-regional and distant recurrence occurred in 6 patients (2.5%). There 16 deaths due to disease and 5 noncancer deaths. The results of the univariable analysis for LRC, DFS, and OS are shown in [Table 2]. Tumor grade, margin status, and LN ratio were significant factors influencing LRR and DFS. Human epidermal growth factor receptor 2 (HER2)/neu positivity and triple negative hormone receptor status showed a trend for prediction of LRC. Thus, the factors included pathological tumor size, margin status, LN ratio as continuous variables and grade and triple-negative breast cancer (TNBC) status as categorical variables for LRC as an endpoint as the aim was to define high-risk groups for LRR. The results of the multivariable analysis are shown in [Table 3].
Table 2: Univariate analysis of prognostic factors affecting outcome

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Table 3: Multivariate analysis for loco-regional control

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Nomogram development

Pathological tumor size, grade, distance from the base, LN ratio, and triple receptor negativity were identified to be most powerful predictors of LRC and were considered for nomogram development using LASSO shrinkage model in package. Pathological tumor size was scored from 0 to 40 starting from 1.0 to 5.0 cm with 5 points increase with an increase in tumor size by 0.5 cm each time. Similarly, the range of points for LN ratio was from 0 to 100 and for the base it was 0–30. The two categorical variables were assigned 0–60 (grade) and 0–16 (TNBC). [Figure 1] depicts the nomogram showing predicted the risk of LRR at 5 and 7 years. The mean and median AUC was 0.71 (interquartile range 0.66–0.76) for the 5 years LRC indicative of fair discriminating ability. The predicted 5 years probability for LRC was decreased from 95% to 60% as the total point score increased from 75 to 214 (supplementary material). Thus, based on prediction nomogram patients could be discriminated into 4 groups with significant LRC difference (P ≤ 0.005, log-rank test). [Figure 2] shows the KM curves for LRC for the quartiles used for building the nomogram.
Figure 1: Nomogram showing predicted risk of loco-regional recurrence at 5 and 7 years. LNRatio – Lymphnode ratio = number of lymph nodes positive/number of lymph nodes dissected; pTsize – Pathologic tumor size in centimeters; Base – Distance of base from tumor in millimeter; Grade – Grade grouping scored as 1 if Grade I or Grade II and scored as 2 if Grade III; TNBC – Triple negative breast cancer scored as 0 if non-TNBC and 1 if TNBC; OS prob – Overall survival probability. As an example if patient with tumor size of 5 cm (40 points), 7 mm from base (0 points), Grade III tumor (60 points), lymph node ratio of 5 (score 15) and non-TNBC receptor status (0 points) will have total points of 115 and predicted LRC is between 90% and 95%. TNBC = Triple negative breast cancer; LRC = Loco-regional control

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Figure 2: Kaplan–Meier curves for the four groups derived for predictive nomogram. The difference in the survival among these groups was statistically significant as estimated by log rank test

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 » Discussion Top

Many nonrandomized studies evaluating outcomes in patients of EBC postupfront mastectomy have shown LRR rate ranging from 5% to 20% subject to heterogeneity among the studies in terms of patient eligibility criteria and characteristics of the study cohort, treatment era as well as variability in the standard of care delivered.[11],[12],[13] Notably, in many of these studies, the details of the systemic treatment have not been reported. In fact, studies reporting the use of anthracycline or taxane-based chemotherapy which is the current standard of care for systemic therapy, have also variably reported the risk of LRR.[14] Hence, routine use of adjuvant loco-regional radiotherapy in all patients of this subgroup may not be advisable. The recently published Swedish population-based study comparing the outcome of EBC postmastectomy for 1–3 positive nodes across two regions of the country highlights the diversity in the radio-therapeutic treatment policy for this patient cohort.[15]

Given the insufficient evidence from randomized studies, there have been multiple nonrandomized studies reported in the last decade which have assessed the impact of various clinico-pathological risk factors on LRR as well as survival. In general age <40–50 years,[12],[16] tumor size >2 cm,[11] high grade,[17] lympho-vascular invasion,[18] number of positive axillary nodes (1 vs. 2–3),[19] LN ratio ranging from 8% to 25%,[11],[20] extra-capsular extension,[13],[17] hormone receptor status,[13] number of adverse risk factors [21] etc., have been found to be important predictors of outcome in this subgroup of patients.[22],[23],[24],[25],[26],[27] In the current study, tumor size, LN ratio, grade, margins and triple negative status predicted for LRR as well as DFS [Table 2]. A recent Korean multicenter study showed similar results with close resection margin being only independent factor for LRR and age <35 years, T2 stage, high tumor grade, close resection margin being independent risk factors for any first recurrence.[28] Another recently published systematic review by Headon et al. suggests a benefit of PMRT for LRC in these group of patients but fails to identify specific prognostic or predictive factors involved.[29]

The Cambridge PMRT index was constructed by the UK investigators by assigning scores (1–3) to each of the four categories including the number of positive LN/lymphovascular invasion, tumor size, margin status and tumor grade. They recommended PMRT for score ≥3. Based on the Cambridge Index, 95% of our patient cohort [Table 1] would merit PMRT which is a very high proportion. Moreover, the Cambridge index does not take into account the hormone receptor status which as shown from the current as well as earlier reports to be one of the strongest prognostic factors. Thus, risk factors for recurrence vary considerably among different study populations, and it is desirable to have careful selection criteria based on institutional data. Till the time results from randomized studies are published, each patient should be carefully evaluated and selected for adjuvant radiotherapy based on both the best clinical evidence and clinician's experience.

Nomograms serve as a useful, statistically based tool for decision making for clinicians as well as patients. These can be constructed on institutional data sets and used for decision making in an individual patient with respect to specific outcomes (e.g., ipsilateral breast relapse after breast conservation, axillary LN metastases after positive axillary ultrasound). In the clinic, it is important to individualize treatment for which estimation of the overall risk of recurrence is advisable. The knowledge of conventional risk factors cannot accurately predict individual patient risk due to the significant interactions among them. Moreover, nomogram also allow inclusion of risk factors as continuous variables (e.g., tumor size, LN ratio, margin width in the current study) as against the conventional factors which are usually analyzed after categorizing the numerical data. In the nomogram, the horizontal width of the line belonging to a factor indicates the strength of the influence. Once developed it is important to do external validation of the nomogram on separate data set but with similar characteristics, otherwise discordant results have been reported earlier.[30],[31]

The risk estimated from the nomogram predicted for individual patient has more practical implications as it accounts for the numerical and categorical data as well as its interaction. Apart from a single study from China which has reported the nomogram approach for EBC with 1–3 positive LNs, authors have not come across other reports in this regard.[32] However, the Chinese study evaluated all the patients together irrespective of receipt of PMRT. Patients receiving adjuvant radiation accounted for one-fourth of the total cohort. Although the authors report a C-index of 0.75, neither internal nor external validation of the nomogram has been discussed either in the same publication or separately. In contrast to this study, patients receiving PMRT were excluded from the current analysis as it was expected to be the strongest factor leading to biased results of the nomogram. Moreover, the current nomogram was thoroughly validated internally to achieve consistent results and account for the low events per variable.

Our study has a few limitations, number of patients was relatively small and exact treatment details of chemotherapy regimens were not available. However, during the study period, anthracycline or taxane-based regimens were standard in our institutional practice. HER2/neu receptor 2+ on immunohistochemistry was not confirmed with more advanced technique and the status of the same was not known in 11% of the patients. This was because HER2/neu status assessment was not standard during that time. In addition, the number of events for the endpoint under consideration is relatively few and is typical of the cohort of EBC being discussed here due to more effective systemic therapies. This could reduce the predictive ability of the nomogram and account for relatively low AUC. Moreover, few of the LRRs, especially internal mammary and deep supraclavicular fossa recurrence may not be detected clinically and later manifest as secondary dissemination thereby affecting DFS. Nevertheless, until the results of the SUPREMO trial become available, the nomogram would be helpful in the prediction of individual risk and aid decision making after independent external validation in separate cohort with similar characteristics.

 » Conclusion Top

In consideration of adjuvant loco-regional radiotherapy of breast cancers with T1, T2 tumors with one to three positive axillary nodes, high-risk histopathological factors need to be taken into account to identify subgroup of patients who will benefit from PMRT. The nomogram developed based on institutional data can be a valuable tool in guiding adjuvant radiation therapy depending on the risk of LRR.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

 » References Top

Overgaard M, Hansen PS, Overgaard J, Rose C, Andersson M, Bach F, et al. Postoperative radiotherapy in high-risk premenopausal women with breast cancer who receive adjuvant chemotherapy. Danish Breast Cancer Cooperative Group 82b Trial. N Engl J Med 1997;337:949-55.  Back to cited text no. 1
Overgaard M, Jensen MB, Overgaard J, Hansen PS, Rose C, Andersson M, et al. Postoperative radiotherapy in high-risk postmenopausal breast-cancer patients given adjuvant tamoxifen: Danish Breast Cancer Cooperative Group DBCG 82c randomised trial. Lancet 1999;353:1641-8.  Back to cited text no. 2
Abe O, Abe R, Enomoto K, Kikuchi K, Koyama H, Masuda H, et al. Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: An overview of the randomised trials. Lancet 2005;366:2087-106.  Back to cited text no. 3
Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thürlimann B, et al. Personalizing the treatment of women with early breast cancer: Highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol 2013;24:2206-23.  Back to cited text no. 4
Recht A, Edge SB, Solin LJ, Robinson DS, Estabrook A, Fine RE, et al. Postmastectomy radiotherapy: Clinical practice guidelines of the American Society of Clinical Oncology. J Clin Oncol 2001;19:1539-69.  Back to cited text no. 5
McGale P, Taylor C, Correa C, Cutter D, Duane F, Ewertz M, et al. Effect of radiotherapy after mastectomy and axillary surgery on 10-year recurrence and 20-year breast cancer mortality: Meta-analysis of individual patient data for 8135 women in 22 randomised trials. Lancet 2014;383:2127-35.  Back to cited text no. 6
Carlson RW, Allred DC, Anderson BO, Burstein HJ, Carter WB, Edge SB, et al. Breast cancer. Clinical practice guidelines in oncology. J Natl Compr Canc Netw 2009;7:122-92.  Back to cited text no. 7
Gourgou-Bourgade S, Cameron D, Poortmans P, Asselain B, Azria D, Cardoso F, et al. Guidelines for time-to-event end point definitions in breast cancer trials: Results of the DATECAN initiative (Definition for the Assessment of Time-to-event Endpoints in CANcer trials). Ann Oncol 2015;26:873-9.  Back to cited text no. 8
Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361-87.  Back to cited text no. 9
Xiao N, Xu QS, Li MZ. hdnom: Building nomograms for penalized cox models with high-dimensional survival data. bioRxiv 2016;  Back to cited text no. 10
Duraker N, Demir D, Bati B, Yilmaz BD, Bati Y, Çaynak ZC, et al. Survival benefit of post-mastectomy radiotherapy in breast carcinoma patients with T1-2 tumor and 1-3 axillary lymph node(s) metastasis. Jpn J Clin Oncol 2012;42:601-8.  Back to cited text no. 11
Moo TA, McMillan R, Lee M, Stempel M, Patil S, Ho A, et al. Selection criteria for postmastectomy radiotherapy in t1-t2 tumors with 1 to 3 positive lymph nodes. Ann Surg Oncol 2013;20:3169-74.  Back to cited text no. 12
Kong M, Hong SE. Which patients might benefit from postmastectomy radiotherapy in breast cancer patients with T1-2 tumor and 1-3 axillary lymph nodes metastasis? Cancer Res Treat 2013;45:103-11.  Back to cited text no. 13
Cosar R, Uzal C, Tokatli F, Denizli B, Saynak M, Turan N, et al. Postmastectomy irradiation in breast in breast cancer patients with T1-2 and 1-3 positive axillary lymph nodes: Is there a role for radiation therapy? Radiat Oncol 2011;6:28.  Back to cited text no. 14
Nordenskjöld AE, Fohlin H, Albertsson P, Arnesson LG, Chamalidou C, Einbeigi Z, et al. No clear effect of postoperative radiotherapy on survival of breast cancer patients with one to three positive nodes: A population-based study. Ann Oncol 2015;26:1149-54.  Back to cited text no. 15
Su YL, Li SH, Chen YY, Chen HC, Tang Y, Huang CH, et al. Post-mastectomy radiotherapy benefits subgroups of breast cancer patients with T1-2 tumor and 1-3 axillary lymph node(s) metastasis. Radiol Oncol 2014;48:314-22.  Back to cited text no. 16
Tendulkar RD, Rehman S, Shukla ME, Reddy CA, Moore H, Budd GT, et al. Impact of postmastectomy radiation on locoregional recurrence in breast cancer patients with 1-3 positive lymph nodes treated with modern systemic therapy. Int J Radiat Oncol Biol Phys 2012;83:e577-81.  Back to cited text no. 17
Matsunuma R, Oguchi M, Fujikane T, Matsuura M, Sakai T, Kimura K, et al. Influence of lymphatic invasion on locoregional recurrence following mastectomy: Indication for postmastectomy radiotherapy for breast cancer patients with one to three positive nodes. Int J Radiat Oncol Biol Phys 2012;83:845-52.  Back to cited text no. 18
He ZY, Wu SG, Zhou J, Li FY, Lin Q, Lin HX, et al. Postmastectomy radiotherapy improves disease-free survival of high risk of locoregional recurrence breast cancer patients with T1-2 and 1 to 3 positive nodes. PLoS One 2015;10:e0119105.  Back to cited text no. 19
Truong PT, Lesperance M, Culhaci A, Kader HA, Speers CH, Olivotto IA. Patient subsets with T1-T2, node-negative breast cancer at high locoregional recurrence risk after mastectomy. Int J Radiat Oncol Biol Phys 2005;62:175-82.  Back to cited text no. 20
Wu SG, He ZY, Li FY, Wang JJ, Guo J, Lin Q, et al. The clinical value of adjuvant radiotherapy in patients with early stage breast cancer with 1 to 3 positive lymph nodes after mastectomy. Chin J Cancer 2010;29:668-76.  Back to cited text no. 21
Katz A, Strom EA, Buchholz TA, Theriault R, Singletary SE, McNeese MD. The influence of pathologic tumor characteristics on locoregional recurrence rates following mastectomy. Int J Radiat Oncol Biol Phys 2001;50:735-42.  Back to cited text no. 22
Woodward WA, Strom EA, Tucker SL, Katz A, McNeese MD, Perkins GH, et al. Locoregional recurrence after doxorubicin-based chemotherapy and postmastectomy: Implications for breast cancer patients with early-stage disease and predictors for recurrence after postmastectomy radiation. Int J Radiat Oncol Biol Phys 2003;57:336-44.  Back to cited text no. 23
Taghian A, Jeong JH, Mamounas E, Anderson S, Bryant J, Deutsch M, et al. Patterns of locoregional failure in patients with operable breast cancer treated by mastectomy and adjuvant chemotherapy with or without tamoxifen and without radiotherapy: Results from five National Surgical Adjuvant Breast and Bowel Project randomized clinical trials. J Clin Oncol 2004;22:4247-54.  Back to cited text no. 24
Truong PT, Olivotto IA, Kader HA, Panades M, Speers CH, Berthelet E. Selecting breast cancer patients with T1-T2 tumors and one to three positive axillary nodes at high postmastectomy locoregional recurrence risk for adjuvant radiotherapy. Int J Radiat Oncol Biol Phys 2005;61:1337-47.  Back to cited text no. 25
Livi L, Saieva C, Detti B, Meattini I, Susini T, Paiar F, et al. Loco-regional recurrence in 2064 patients with breast cancer treated with mastectomy without adjuvant radiotherapy. Eur J Surg Oncol 2007;33:977-81.  Back to cited text no. 26
Mukesh MB, Duke S, Parashar D, Wishart G, Coles CE, Wilson C. The Cambridge post-mastectomy radiotherapy (C-PMRT) index: A practical tool for patient selection. Radiother Oncol 2014;110:461-6.  Back to cited text no. 27
Park HJ, Shin KH, Kim JH, Ahn SD, Kim JY, Park W, et al. Incorporating risk factors to identify the indication of post-mastectomy radiotherapy in N1 breast cancer treated with optimal systemic therapy: A multicenter analysis in Korea (KROG 14-23). Cancer Res Treat. 2016 Oct 19. doi: 10.4143/crt.2016.405. [Epub ahead of print].  Back to cited text no. 28
Headon H, Kasem A, Almukbel R, Mokbel K. Improvement of survival with postmastectomy radiotherapy in patients with 1-3 positive axillary lymph nodes: A systematic review and meta-analysis of the current literature. Mol Clin Oncol 2016;5:429-36.  Back to cited text no. 29
Kindts I, Laenen A, Peeters S, Janssen H, Depuydt T, Neven P, et al. Evaluation of a breast cancer nomogram to predict ipsilateral breast relapse after breast-conserving therapy. Radiother Oncol 2016;119:45-51.  Back to cited text no. 30
Yi M, Meric-Bernstam F, Kuerer HM, Mittendorf EA, Bedrosian I, Lucci A, et al. Evaluation of a breast cancer nomogram for predicting risk of ipsilateral breast tumor recurrences in patients with ductal carcinoma in situ after local excision. J Clin Oncol 2012;30:600-7.  Back to cited text no. 31
Shen H, Zhao L, Wang L, Liu X, Liu X, Liu J, et al. Postmastectomy radiotherapy benefit in Chinese breast cancer patients with T1-T2 tumor and 1-3 positive axillary lymph nodes by molecular subtypes: An analysis of 1369 cases. Tumour Biol 2016;37:6465-75.  Back to cited text no. 32


  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3]

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