Do PARP Inhibitor Cancer Drugs Affect Blood Sugar, Thyroid, and Cholesterol? A Major Review of 26 Trials

Table of Contents

• Key Points
• Background: Why This Research Matters
• How the Research Was Conducted
• Who Was Studied
• Key Finding: High Blood Sugar (Hyperglycemia)
• Key Finding: Low Blood Sugar (Hypoglycemia)
• Key Finding: Type 2 Diabetes
• Key Finding: Thyroid Function
• Key Finding: Cholesterol and Triglycerides
• Quality of the Studies
• What This Means for Patients
• Limitations: What the Study Could Not Prove
• Recommendations for Patients and Doctors
• Frequently Asked Questions
• Source Information

Key Points

• In a meta-analysis of 26 trials with 9,590 patients, PARP inhibitors as a group did not significantly raise the risk of most endocrine or metabolic problems.
• Niraparib was linked to more than double the odds of high blood sugar (odds ratio 2.15); close blood sugar monitoring is recommended for patients taking it.
• Patients with metastatic pancreatic cancer receiving PARP inhibitors were more susceptible to high blood sugar (odds ratio 1.78) in a subgroup analysis.
• Rucaparib appeared to possibly lower the risk of high blood sugar (odds ratio 0.54), though the reason for this difference is unclear.
• Half of the included trials were rated low quality due to high risk of bias, so results should be interpreted with caution.

Background: Why This Research Matters

PARP inhibitors (poly [ADP-ribose] polymerase inhibitors, often shortened to PARPi) have changed the way doctors treat many solid tumors. These drugs were first developed for cancers linked to BRCA1 and BRCA2 gene mutations. They work by blocking PARP enzymes, which cancer cells rely on to repair their DNA. When DNA repair fails, the cancer cells die.

Doctors now use PARP inhibitors for ovarian cancer, breast cancer, lung cancer, and metastatic castration-resistant prostate cancer (mCRPC, a form of prostate cancer that no longer responds to hormone-lowering treatment). Newer research also explores their use in pancreatic cancer and gastric cancer (stomach cancer).

These drugs have real benefits, but they also cause side effects. Common problems include nausea, vomiting, anemia (low red blood cell counts), diarrhea, low platelet counts, low white blood cell counts, and high blood pressure. Doctors must manage these side effects carefully.

An important question has been whether PARP inhibitors also affect the body's endocrine system (the hormone-producing glands) and metabolic system (the processes that turn food into energy). Laboratory studies suggested that PARP inhibitors might actually protect against these kinds of problems. However, evidence from patients was scarce and inconclusive.

Some patients taking olaparib for ovarian cancer developed hypothyroidism (an underactive thyroid gland). Other patients taking olaparib or rucaparib developed hyperglycemia (high blood sugar). Early evidence also suggested that olaparib and rucaparib might affect lipid metabolism (how the body processes fats), possibly leading to dyslipidemia (abnormal levels of fats in the blood).

These endocrine and metabolic complications are uncommon and do not affect every patient. Still, strong clinical evidence was lacking. This meta-analysis (a study that combines results from many trials) was designed to fill that gap.

How the Research Was Conducted

The researchers registered their plan in advance in the PROSPERO database (an international registry of systematic reviews) under the ID CRD42023457959. They followed the PRISMA reporting guidelines, which are standard rules for conducting and reporting systematic reviews.

The team searched Medline, EMBASE, PubMed, and Web of Science, plus the ClinicalTrials.gov registry. The search covered January 1, 1988, to November 18, 2023, and was limited to English-language publications. Search terms included "PARP," "olaparib," "rucaparib," "niraparib," "talazoparib," "veliparib," "iniparib," "fuzuloparib," and "randomized controlled trials."

Two authors ran the search independently. The team also looked for grey literature (research not published in standard journals) and conference abstracts. Safety data from ClinicalTrials.gov were included even when no corresponding journal publication existed.

Which studies were included:

• Phase II or Phase III randomized controlled trials (RCTs, trials in which patients are randomly assigned to treatment groups)
• Trials comparing a PARP inhibitor against a placebo or a non-placebo control
• Patients aged 18 and older with a solid tumor diagnosis

Which studies were excluded:

• Case studies and observational studies
• Non-randomized trials
• Reviews and guidelines
• Conference articles and Phase I studies
• Trials in which both groups received a PARP inhibitor

The outcomes of interest were metabolic and endocrine dysfunctions. These included hyperglycemia (high blood sugar) and hypoglycemia (low blood sugar), type 2 diabetes, hyperthyroidism (overactive thyroid) and hypothyroidism (underactive thyroid), hypertriglyceridemia (high triglyceride levels), and hypercholesterolemia (high cholesterol).

Three authors reviewed full texts, abstracts, and titles to select studies. Four authors extracted data in pairs. A third author resolved any disagreements. The team used Covidence software (an online tool by Veritas Health Innovation) to manage the data extraction. When information was missing or unclear, the researchers contacted study authors at least twice.

Two investigators assessed study quality using the Cochrane Risk of Bias 2.0 Tool with RevMan V5.4.21 software. This tool rates trials across five areas: randomization, allocation concealment, blinding, incomplete outcome data, and selective reporting. Each area was rated as low risk, uncertain risk, or high risk of bias. A separate adjudicator resolved disagreements.

The researchers measured how often each condition occurred in each study. They calculated odds ratios (OR) and confidence intervals (CI) using the Peto approach. An odds ratio compares the odds of an event in one group with the odds in another group. A confidence interval shows the range of values likely to contain the true result.

Statistical heterogeneity (how much the trials differed from one another) was assessed with Cochrane's Q statistic and the I² statistic. The team chose between random-effects and fixed-effects models based on the observed heterogeneity. They ran subgroup analyses by type of base therapy, PARP inhibitor variant, and solid tumor type. Publication bias was assessed with Egger's test and Begg's test, plus a sensitivity analysis. Data management used Microsoft Office Excel 2007, and statistical analyses used RevMan Manager and Stata software version 15.

Who Was Studied

The initial search found 5,236 studies. Of these, 200 underwent full evaluation. The team excluded 40 conference proceedings, 127 studies that did not examine endocrine or metabolic outcomes, and 7 cross-sectional studies.

After rigorous review, 26 articles were selected for analysis. The final hyperglycemia analysis included 21 studies. Other analyses included 3 articles on hyperthyroidism, 6 on type 2 diabetes, 5 on hypercholesterolemia, 4 on hypoglycemia, 5 on hypothyroidism, and 4 on hypertriglyceridemia.

In total, data from 30 RCTs covering 9,590 patients were included. The agreement between reviewers during full-text screening was substantial, with a kappa statistic of 0.77. (The kappa statistic measures how much reviewers agree beyond what would be expected by chance.)

Cancer types among the patients:

• Ovarian cancer: 3,533 patients (36.84%)
• Breast cancer: 3,640 patients (37.95%)
• Lung cancer: 1,030 patients (10.74%)
• Prostate cancer: 934 patients (9.73%)
• Pancreatic cancer: 271 patients (2.82%)
• Urothelial carcinoma (cancer of the urinary tract lining): 212 patients (2.21%)
• Colorectal cancer: 130 patients (1.35%)

The included trials covered 16 Phase III trials and 10 Phase II trials. The PARP inhibitors studied were olaparib, rucaparib, niraparib, veliparib, and iniparib. Control groups received placebo, chemotherapy, or other standard treatments.

Key Finding: High Blood Sugar (Hyperglycemia)

This was the largest analysis in the study. Twenty-five RCTs with 7,190 patients were examined. Of these, 4,120 patients were in the PARP inhibitor group and 3,070 patients were in the control group.

In the PARP inhibitor group, 279 of 4,120 patients developed any-grade hyperglycemia. This is an incidence of 6.77%. In the control group, 182 of 3,070 patients developed hyperglycemia, an incidence of 5.92%.

When all PARP inhibitors were analyzed together, the drugs did not significantly increase the odds of any-grade hyperglycemia (OR = 1.20, 95% CI 0.98–1.46; P = 0.076). The result fell just short of statistical significance. There was no significant heterogeneity across the trials (χ² = 35.30, P = 0.064; I² = 32.0%).

However, subgroup analyses revealed important differences between individual drugs and between cancer types.

Niraparib and high blood sugar: Treatment with niraparib was linked to a significantly increased risk of hyperglycemia (OR = 2.15, 95% CI 1.28–3.62; P = 0.004). This means patients taking niraparib had more than double the odds of developing high blood sugar compared with the control group.

Rucaparib and high blood sugar: Rucaparib showed a possible protective effect. Patients taking rucaparib had lower odds of hyperglycemia (OR = 0.54, 95% CI 0.30–0.97; P = 0.039).

Pancreatic cancer patients: Patients with metastatic pancreatic cancer receiving PARP inhibitors were more susceptible to hyperglycemia (OR = 1.78, 95% CI 1.04–3.04; P = 0.036).

Subgroup analyses by type of PARP inhibitor-based therapy showed no significant variations. Sensitivity analyses confirmed that the results were stable. No evidence of publication bias was found based on the Egger test (P = 0.322), the Begg test (P = 0.661), or the funnel plot.

Serious hyperglycemia: Data from 2 studies covering 352 patients showed that serious hyperglycemia occurred in 0.4% of patients receiving PARP inhibitors (1 event among 226 patients). In the control group, serious hyperglycemia occurred in 0.7% of patients (1 event among 126 patients). PARP inhibitor therapy showed no significant increase in the risk of serious hyperglycemia (OR = 0.55, 95% CI 0.03–9.95; P = 0.688). This analysis showed no significant heterogeneity (χ² = 1.79, P = 0.181; I² = 44.2%).

For context, the researchers noted that hyperglycemia at 6.77% was notably less frequent than other side effects of PARP inhibitors. Nausea occurred in 68.8% of patients, vomiting in 47.8%, anemia in 47.8%, diarrhea in 25.3%, low platelet counts in 23.0%, low white blood cell counts in 39.6%, and high blood pressure in 12%.

Key Finding: Low Blood Sugar (Hypoglycemia)

Four studies with 1,339 patients assessed hypoglycemia. Of these, 854 patients received PARP inhibitor therapy and 485 patients were in the control group.

Hypoglycemia occurred in 0.5% of the PARP inhibitor group (5 events among 854 patients). In the control group, hypoglycemia occurred in 0.4% of patients (2 events among 485 patients).

The analysis found no significant difference in hypoglycemia risk between the two groups (OR = 1.51, 95% CI 0.32–7.05; P = 0.603). Heterogeneity analysis showed no notable differences across the studies (χ² = 2.66, P = 0.447; I² = 0.0%).

Key Finding: Type 2 Diabetes

Six studies with 2,916 patients evaluated type 2 diabetes. The incidence of type 2 diabetes among patients receiving PARP inhibitors was 0.1% (4 cases among 1,701 patients). In the control group, the incidence was 0.2% (3 cases among 1,215 patients).

The analysis found no significant difference in the risk of type 2 diabetes compared with control (OR = 0.99, 95% CI 0.22–4.54; P = 0.993). The findings showed no heterogeneity in this analysis (χ² = 6.93, P = 0.226; I² = 27.8%).

Key Finding: Thyroid Function

Hyperthyroidism (overactive thyroid): Three studies with 1,275 patients were analyzed. Of these, 641 patients received PARP inhibitors and 634 patients received standard treatment. Hyperthyroidism occurred in 4 of 641 patients taking PARP inhibitors, an incidence of 0.6%. In the control group, 3 of 634 patients developed hyperthyroidism, an incidence of 0.4%.

PARP inhibitors did not significantly affect the likelihood of developing hyperthyroidism (OR = 1.32, 95% CI 0.30–5.85; P = 0.714). The analysis showed no significant heterogeneity (χ² = 2.07, P = 0.356; I² = 3.2%).

Hypothyroidism (underactive thyroid): Five studies with 3,224 patients were examined. Hypothyroidism occurred in 15 of 1,752 patients taking PARP inhibitors, an incidence of 0.8%. In the control group, 10 patients developed hypothyroidism, an incidence of 0.6%.

Key Finding: Cholesterol and Triglycerides

Hypercholesterolemia (high cholesterol): This analysis included 2,157 patients. High cholesterol occurred in 3.67% of patients receiving PARP inhibitors (51 cases among 1,389 patients). In the control group, high cholesterol occurred in 2.47% of patients (19 cases among 768 patients).

PARP inhibitors did not significantly increase the risk of hypercholesterolemia (OR = 1.62, 95% CI 0.98–2.69; P = 0.060). This result approached but did not reach statistical significance. The analysis showed no significant heterogeneity (χ² = 6.68, P = 0.154; I² = 40.1%).

The study also examined hypertriglyceridemia (high triglycerides) in four studies. No statistically significant differences were observed for this outcome or for the other outcomes associated with PARP inhibitor use.

Quality of the Studies

The researchers assessed study quality using the Cochrane Collaboration guidelines. All included studies were identified as carrying some risk of bias. Only seven studies were deemed of high quality. Fourteen studies were categorized as being at high risk of bias.

Overall, 50% of the included randomized controlled trials were assessed as low quality due to high risk of bias. This is an important limitation because it means the results should be interpreted with some caution.

What This Means for Patients

This meta-analysis provides the most comprehensive picture to date of how PARP inhibitors affect endocrine and metabolic health in patients with solid tumors. The findings challenge the earlier laboratory suggestion that PARP inhibitors might protect against these problems.

For most patients, PARP inhibitors did not significantly raise the risk of thyroid problems, type 2 diabetes, low blood sugar, high cholesterol, or high triglycerides. The overall incidence of these conditions was low.

However, the picture differs for specific drugs and specific patient groups. Niraparib was clearly linked to an increased risk of high blood sugar. Patients with metastatic pancreatic cancer were also more vulnerable to high blood sugar when taking PARP inhibitors.

Interestingly, rucaparib appeared to have the opposite effect, potentially reducing the risk of high blood sugar. The reasons for this difference between drugs remain unclear.

The researchers emphasized that the underlying mechanisms of how PARP inhibitors affect endocrine and metabolic functions are still not understood. PARP1, the main enzyme targeted by these drugs, regulates inflammation, gene transcription, and cellular energy use. All of these processes are connected to endocrine and metabolic disorders. This biological connection may explain why these drugs can affect blood sugar and hormone levels.

Limitations: What the Study Could Not Prove

Several important limitations affect how these results should be interpreted.

• Study quality: Half of the included randomized controlled trials were assessed as low quality due to high risk of bias. Only seven studies were rated as high quality.
• Missing data: Some trials did not report endocrine and metabolic adverse events. The researchers had to contact authors and sponsors to obtain missing information, and some data may still be incomplete.
• Unclear mechanisms: The biological reasons why PARP inhibitors affect endocrine and metabolic functions remain unknown.
• Limited patient numbers for some outcomes: Some analyses, such as serious hyperglycemia and hypoglycemia, included very few patients and events. This limits the reliability of those specific findings.
• Subgroup findings need confirmation: The differences between niraparib and rucaparib, and the higher risk in pancreatic cancer patients, come from subgroup analyses. These findings should be confirmed in future studies.

The authors noted that endocrine and metabolic complications with PARP inhibitors are uncommon and not universal among patients. The scarcity of robust clinical evidence before this study was a significant research gap.

Recommendations for Patients and Doctors

Based on these findings, the researchers made specific recommendations for clinical practice.

1. Monitor blood sugar closely during niraparib treatment. Patients taking niraparib should have their blood sugar checked regularly, because this drug was linked to more than double the odds of high blood sugar.
2. Pay special attention to pancreatic cancer patients. Patients with metastatic pancreatic cancer receiving PARP inhibitors were more susceptible to high blood sugar and should be monitored carefully.
3. Continue routine monitoring for other conditions. Even though most endocrine and metabolic problems were not significantly increased, doctors should remain alert for thyroid changes, cholesterol changes, and blood sugar changes in all patients taking PARP inhibitors.
4. Report symptoms promptly. Patients should tell their care team about symptoms such as excessive thirst, frequent urination, unexplained fatigue, weight changes, or feeling unusually cold or warm. These can be signs of blood sugar or thyroid problems.
5. More research is needed. The authors called for further comprehensive research to understand how PARP inhibitors affect endocrine and metabolic functions.

The study's conclusion was clear: PARP inhibitors may have adverse effects on endocrine and metabolic pathways. Close monitoring of hyperglycemia is recommended for patients undergoing niraparib therapy, especially those with pancreatic cancer.

Frequently Asked Questions

What did this review find about PARP inhibitors and blood sugar?

When all PARP inhibitors were analyzed together, they did not significantly raise the odds of any-grade high blood sugar (odds ratio 1.20, 95% confidence interval 0.98–1.46). However, one drug, niraparib, was linked to more than double the odds of high blood sugar, while rucaparib appeared to possibly lower that risk.

Which PARP inhibitor was linked to high blood sugar?

Niraparib was linked to a significantly increased risk of high blood sugar, with an odds ratio of 2.15 (95% confidence interval 1.28–3.62). This means patients taking niraparib had more than double the odds of developing high blood sugar compared with the control group. The authors recommend close blood sugar monitoring for patients taking niraparib.

Are pancreatic cancer patients more at risk of high blood sugar on PARP inhibitors?

Yes. In a subgroup analysis, patients with metastatic pancreatic cancer receiving PARP inhibitors were more susceptible to high blood sugar (odds ratio 1.78, 95% confidence interval 1.04–3.04). The authors recommend that these patients be monitored carefully for blood sugar changes. This finding comes from a subgroup analysis and should be confirmed in future studies.

Did the review find any effect on thyroid function?

No significant effect was found. Hyperthyroidism occurred in 0.6% of patients taking PARP inhibitors versus 0.4% in controls, with no significant difference (odds ratio 1.32, 95% confidence interval 0.30–5.85). Hypothyroidism occurred in 0.8% of patients on PARP inhibitors versus 0.6% in controls. These conditions were uncommon in both groups.

What about cholesterol and triglyceride levels?

PARP inhibitors did not significantly increase the risk of high cholesterol (odds ratio 1.62, 95% confidence interval 0.98–2.69), though the result approached significance. High triglycerides also showed no statistically significant difference. The authors still recommend that doctors remain alert for cholesterol changes in all patients taking PARP inhibitors.

What symptoms should patients report to their care team?

Patients should promptly tell their care team about symptoms such as excessive thirst, frequent urination, unexplained fatigue, weight changes, or feeling unusually cold or warm. These can be signs of blood sugar or thyroid problems. Reporting them early allows doctors to monitor and manage any endocrine or metabolic issues that may arise during PARP inhibitor treatment.

If I'm starting niraparib for ovarian cancer, when should I get a second opinion about blood sugar monitoring?

Niraparib is linked to more than double the odds of high blood sugar, so patients taking it should have blood sugar checked regularly. A second opinion can help confirm whether your monitoring plan matches this risk, especially if you have metastatic pancreatic cancer, which is also linked to higher hyperglycemia risk. It can also address whether rucaparib's possibly lower blood sugar risk is relevant to your situation. Bring your pathology reports, imaging, and treatment history. Diagnostic Detectives Network provides independent expert second opinions.

Source Information

Original article title: Incidence and risk of endocrine and metabolic abnormalities linked to PARP inhibitors in solid tumors: a meta-analysis.

Authors: Fu S, Zou P, Fang Z, Zhou X, Chen J, Gong C, Quan L, Lin B, Chen Q, Lang J, Chen M.

Publication: BMC Cancer (2025) 25:183

DOI: https://doi.org/10.1186/s12885-025-13579-1

Trial registration: PROSPERO database, ID CRD42023457959

Note: This patient-friendly article is based on peer-reviewed research. It is intended for educational purposes and should not replace discussion with your healthcare provider. Always talk to your doctor about your specific treatment plan and any symptoms you experience.