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Cancer patients’ preferences for therapy decisions can be grouped into categories and separated by demographic factors

  • Original Article – Clinical Oncology
  • Published:
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Abstract

Purpose

Shared decision-making is based on comparable understanding of decision criteria on both sides that requires knowledge about preferences, reception/prioritization of benefits and covariates influencing these criteria. We addressed identification of cancer patients’ preferences for treatment decisions and covariates for preference patterns in certain patient cohorts.

Design

Using preference surveys ordinal ranking of decisional preferences in life (PL) and during therapy (PT) were obtained and aggregated by factorial analysis. Demographic and clinical data enabled clustering of patient groups including non-malignant control group with distinct preference patterns. Covariates for these patterns were determined by multivariate ANOVA.

Results

1777 cancer and 367 non-oncological patients (≥18 years) were evaluable (response 56.0%). Patient-reported PT was grouped into distinctive categories: immediate treatment effectivity, long-term effects and survival, empathy, easy treatment and employability/healing. Gender, parenthood, family status, age and educational level mainly determine importance of PL (52.1% variance) and PT (55.1% variance) enabling discrimination of specific preference patterns in patients: older males, non-single, younger males, non-single female with children and young, single patients without children that mainly significantly differed from non-cancer patients (p < 0.001).

Conclusion

Relevance of decisional PL/PT appears to be cancer-specific and distinct between cancer patient groups. If patients recognize direct social responsibility, immediate treatment effects gain importance accompanied by reduced impact of employability, rehabilitation and financial security. For young and independent patients empathy has similar impact as treatment effects. Consequently, clinical research should consider age-specific endpoints and distinct decisional preferences to match patients’ perspective by specific evidence.

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Acknowledgements

The authors thank Prof. Klaus Backhaus (Institute for Assets and System Technology Münster, Germany) for his great support in statistics and methodology.

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Authors and Affiliations

  1. Comprehensive Cancer Center Münster, University Hospital Münster, Münster, Germany

    Jana Arnholdt

  2. University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Martinistr. 52 (O24), 20246, Hamburg, Germany

    Jörg Haier

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  1. Jana Arnholdt
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  2. Jörg Haier
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Corresponding author

Correspondence to Jörg Haier.

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Conflict of interest

All authors declare that they do not have any potential conflict of interests regarding the contents of this study. JH is publicly funded by EU, DFG, DKH and he is advisor for ICME Health Care.

Electronic supplementary material

Below is the link to the electronic supplementary material.

432_2017_2390_MOESM1_ESM.jpg

Figure 1 (Supplement 1) Interrelation of various PT factors and the influence of demographic characteristics on their expression are shown in for age dependent distribution of PT “Immediate treatment effectivity” and PT “Employability and healing” as example. These results suggested distinct patient groups defined by demographic profiles that discriminate their therapy decision preferences. (JPG 53 KB)

Figure 2 (Supplement 2) Cluster size and predictor importance for different cluster solutions. (JPG 119 KB)

432_2017_2390_MOESM3_ESM.jpg

Figure 3 (Supplement 3) Correlation between PL “Physical and social health” and PT “Immediate treatment effectivity”. 34% of the variance can be explained by this relationship. (R2 = 0.337) Filled line: correlation function, dotted lines: 95% confidence interval. (JPG 54 KB)

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Supplementary material 5 (PDF 62 KB)

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Arnholdt, J., Haier, J. Cancer patients’ preferences for therapy decisions can be grouped into categories and separated by demographic factors. J Cancer Res Clin Oncol 143, 1573–1584 (2017). https://doi.org/10.1007/s00432-017-2390-x

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  • DOI: https://doi.org/10.1007/s00432-017-2390-x

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