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Fall predictors in hospitalized patients living with cancer: a case–control study

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Abstract

Purpose

To identify fall predictors and develop an assessment tool to be used for screening hospitalized cancer patients at risk for fall.

Methods

A retrospective case–control study was conducted in 2018 at a cancer center in Northern Italy. The study participants were 448 adult cancer patients admitted to the oncology ward from 2009 to 2013. The case group consisted of 112 patients presenting at least one fall, while controls were randomly chosen by matching each case for age, sex, and admission period with three patients who did not fall. Data for the fall predictors were extracted from the electronic medical records. Conditional logistic regression was used to evaluate the association between patient’s characteristics and fall risk.

Results

The overall prevalence of patients having at least one candidate fall predictor was high (98%). Seven of the studied variables showed an independent association with fall risk at multivariate analysis. These were tumor site, the presence of neurologic diseases, gait imbalance disorders, fatigue, and the assumption of certain medications such as diuretics, hypnotics, and opioids (odds ratios and 95% confidence intervals in brackets were 3.78 (1.78–8.13), 2.26 (1.08–4.77), 4.22 (1.87–9.52), 2.76 (1.45–5.26), 2.66 (1.52–4.66), 2.41 (1.20–4.85), and 3.03 (1.68–5.45), respectively).

Conclusions

In this study, we identified falling risk factors in an Italian population of hospitalized cancer patients and developed a new risk assessment tool. An external validation is necessary before implementing our screening tool in clinical practice.

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Data availability

All data relevant to the study are included in the article or uploaded as supplemental information. The authors confirm that the data supporting the findings of this study are available within the article (and/or) its supplemental materials. The authors have full control of primary data and agree to allow the journal to review their data if requested.

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Acknowledgements

The authors are grateful to Ing. Nicola Gentili for providing the electronic selection of controls.

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Authors and Affiliations

  1. Istituto Romagnolo Per Lo Studio Dei Tumori “Dino Amadori” IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy

    Anita Zeneli, Sandra Montalti, Itria Masciangelo, Gloria Manieri, Monica Golinucci, Oriana Nanni, Maria Teresa Montella, Giovanni Martinelli & Elisabetta Petracci

Authors
  1. Anita Zeneli
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  2. Sandra Montalti
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  3. Itria Masciangelo
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  4. Gloria Manieri
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  5. Monica Golinucci
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  7. Maria Teresa Montella
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  8. Giovanni Martinelli
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  9. Elisabetta Petracci
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Contributions

AZ, SM, GM, and MTM designed the study and provided the training of research nurses involved in the study. MG, GM, and IM were involved in data collection and registration. EP was responsible for data analysis. AZ, ON, and EP contributed to the drafting of the manuscript and all authors critically reviewed the draft and approved the final version for submission.

Corresponding author

Correspondence to Anita Zeneli.

Ethics declarations

Ethics approval

The study protocol was approved by the relevant medical, scientific, and ethics committees of Area Vasta of Romagna (Prot. N. 2741/2013/1.5/113) and has been conducted in accordance with good clinical practice and the principles of the Helsinki Declaration.

Consent to participate

Given the retrospective nature of the study, it was not possible to obtain the informed consensus from patients because most of them were not reachable (dead or in critical conditions). In research centers and universities in Italy, the use of patient data for research purposes can be authorized by the General patients Authorization 2018 [32].

Consent for publication

Not applicable. Specific precautions were put in place to warranty the confidentiality of participants. In particular, the study data extracted from the EMRs were initially registered in a dedicated encrypted database with limited access to study nurses only. The completed database was permanently anonymized by deleting patients’ identity data and by assigning a unique numerical code to each study participant.

Competing interests

The authors declare no competing interests.

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Zeneli, A., Montalti, S., Masciangelo, I. et al. Fall predictors in hospitalized patients living with cancer: a case–control study. Support Care Cancer 30, 7835–7843 (2022). https://doi.org/10.1007/s00520-022-07208-x

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  • DOI: https://doi.org/10.1007/s00520-022-07208-x

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