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Adherence to guidelines and breast cancer patients survival: a population-based cohort study analyzed with a causal inference approach

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Purpose

There is a lack of real-world studies evaluating the impact on survival of an evidence-based pathway of care in breast cancer. The aim of this work is to investigate the effect of adherence to guidelines on long-term survival for a cohort of Italian breast cancer patients.

Methods

The cohort included incident female breast cancer cases (2007–12), from the registry of the Milan province (Italy), not metastatic at diagnosis and receiving primary surgery. We selected sets of indicators, according to patient and tumor characteristics. We then defined the pathway of care as adherent to guidelines if it fulfilled at least 80% of the indicators. Indicators were measured using different administrative health databases linked on a unique key. A causal inference approach was used, drawing a directed acyclic graph and fitting an inverse probability weighted marginal structural model, accounting for patient’s demographic, socioeconomic and tumor characteristics.

Results

The analysis included 6333 patients, 69% of them were classified as having an adherent care. Mean age was 61 years (standard deviation, 13.6 years) and half of the patients were in Stage I (50%) at diagnosis. Median follow-up time was 5.6 years. Overall, 5-year survival was 90% (95% CI, 89–91%). The estimated risk of death was 30% lower for patients with adherent than nonadherent care (hazard ratio [HR], 0.66; 95% CI, 0.55–0.77).

Conclusions

Our study confirms, in real-world care, the impact on survival of receiving a care pathway adherent to guidelines in non-metastatic breast cancer patients.

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Abbreviations

CI:

Confidence interval

DAG:

Directed acyclic graph

HR:

Hazard ratio

IPW:

Inverse probability weighted

RCT:

Randomized controlled trial

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Funding

Supported by grant RF-2011-02348959 from the Italian Ministry of Health.

Author information

Authors and Affiliations

  1. Center of Biostatistics for Clinical Epidemiology, School of Medicine and Surgery, University of Milan Bicocca, Via Cadore 48, 20900, Monza, Italy

    Anita Andreano, Paola Rebora & Maria Grazia Valsecchi

  2. Epidemiology Unit, Agency for Health Protection of the Province of Milan, Milan, Italy

    Anita Andreano & Antonio Giampiero Russo

Authors
  1. Anita Andreano
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  2. Paola Rebora
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  3. Maria Grazia Valsecchi
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  4. Antonio Giampiero Russo
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Corresponding author

Correspondence to Anita Andreano.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

All analyses were performed in compliance with the Italian law on health data protection.

Electronic supplementary material

Appendices

Appendix 1: Sensitivity analyses

1. Results of the IPW marginal structural model, assuming proportional hazards, investigating the association between survival and adherence as a dichotomous variable, using different cut-offs to define adherent care. Results, here and in the following section, are presented as the Hazard ratio (HR) of death for adherent vs. nonadherent patients and their 95% confidence intervals (CI).

Cut-off

% of adherent pts

HR (95% CI)

P

60%

84

0.71 (0.58–0.87)

0.001

70%

77

0.63 (0.52–0.76)

<.001

80% (main analysis)

69

0.66 (0.55–0.77)

<.001

90%

38

0.88 (0.73–1.07)

0.21

2. Results of the IPW marginal structural model, assuming proportional hazards, investigating the association between survival and adherence as a four class ordinal variable (cut-points: 20th percentile, corresponding to 67%; 30th percentile, 75%; 60th percentile, 86%), and as a continuous variable. For the ordinal variable, probability of adherence given potential confounders f(A|L), was estimated using a cumulative logistic regression model with the same covariates of the main analysis, with the exception of all first-degree interactions.

Adherence

HR (95% CI)

P

≤67% vs. > 86%

2.83 (2.29–3.45)

<.001

>67 and ≤ 75% vs. > 86%

1.57 (1.14–2.14)

0.005

>75 and ≤ 86% vs. > 86%

1.01 (0.80–1.28)

0.911

For adherence treated as a continuous variable varying between 0 and 100, f(A|L) is a probability density function and it was estimated through a linear regression model, including the same covariates of the main analysis, and then assuming a normal distribution with constant variance. We estimated an IPW marginal structural model for the association between survival and adherence as a flexible function (restricted cubic spline with three knots at 50, 85 and 90%). The graph illustrates the 8-year probability of death for increasing adherence level, which is higher for low adherence percentage and decreases almost linearly up to 80%. This trend motivated the choice of the cut-off for the main analysis presented in the article.

3. Complete cases analysis: we estimated an IPW marginal structural model for the association between survival and adherence assuming proportional hazards using only patients with all necessary potential confounders in the original dataset (3238). Characteristics of this population are described in the table below. The proportion of adherent patients was 69%. The estimated HR was 0.71 (95%CI, 0.57-0.90, P = 0.004).

 

No. of pts 3238

Adherent

No. 2237

Nonadherent

No. 1001

N

%

N

%

Age

 <50 years

654

29.24

298

29.77

 50–69 years

1037

46.36

362

36.16

 >69 years

546

24.41

341

34.07

Grading

 1

241

10.77

99

9.89

 2

1189

53.15

523

52.25

 3

807

36.08

379

37.86

Stage

 1

1143

51.10

439

43.86

 2

780

34.87

402

40.16

 3

314

14.04

160

15.98

Molecular subtype

 Luminal A

817

36.52

375

37.46

 Luminal B

897

40.10

377

37.66

 Luminal Her2

240

10.73

117

11.69

 Her2 type

96

4.29

56

5.59

 Triple negative

187

8.36

76

7.59

N of positive nodes

 0

1431

63.97

618

61.74

 1–3

524

23.42

260

25.97

 4–9

161

7.20

66

6.59

 ≥10

121

5.41

57

5.69

Charlson index

 0

1733

77.47

755

75.42

 1–2

471

21.05

206

20.58

 ≥3

33

1.48

40

4.00

Deprivation index, quintiles

 I

273

12.20

146

14.59

 II

265

11.85

128

12.79

 III

336

15.02

135

13.49

 IV

525

23.47

208

20.78

 V

838

37.46

384

38.36

Marital status

 Never married

238

10.64

113

11.29

 Married

1627

72.73

635

63.44

 Divorced

88

3.93

47

4.70

 Widow

284

12.70

206

20.58

Education

 None or elementary school

713

31.87

370

36.96

 Middle School

606

27.09

230

22.98

 High School

814

36.39

339

33.87

 College and higher

104

4.65

62

6.19

Employment

 Housewife/unemployed

553

24.72

211

21.08

 Workers

242

10.82

90

8.99

 Office worker/teachers

540

24.14

232

23.18

 Managers and professionals

86

3.84

48

4.80

 Retired

816

36.48

420

41.96

4. Results of the IPW marginal structural model, assuming proportional and non-proportional hazards, investigating the association between survival and adherence as a dichotomous variable, excluding patients > 69 years.

No.

% of adherents

Proportional hazard model

Non proportional hazard model

HR (95% CI)

HR(time since diagnosis) (95% CI)

1 year

2 years

5 years

4559

72

0.73

(0.56–0.95)

0.55

(0.36–0.86)

0.58

(0.43–0.80)

1.04

(0.70–1.56)

  1. HR hazard ratio, CI confidence interval

Appendix 2. Distribution of weights

Distribution of stabilized weights derived from the analysis of 50 imputed datasets (missing data imputed by fully conditional specification using MI SAS procedure). Standard errors (SE) have been pooled according to Rubin [39]. Minimum and maximum are the lowest and highest values found across all datasets.

Stabilized weights

Mean

SE

Median

I Q

III Q

Min

Max

Inverse probability of:

Adherence

1.005

0.001

0.958

0.888

1.079

0.328

7.177

Censoring

1.000

0.000

1.000

0.999

1.000

0.949

1.123

Adherence and censoring

1.005

0.001

0.958

0.888

1.079

0.328

7.184

  1. Q quartile, Min minimum, Max maximum

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Andreano, A., Rebora, P., Valsecchi, M.G. et al. Adherence to guidelines and breast cancer patients survival: a population-based cohort study analyzed with a causal inference approach. Breast Cancer Res Treat 164, 119–131 (2017). https://doi.org/10.1007/s10549-017-4210-z

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  • DOI: https://doi.org/10.1007/s10549-017-4210-z

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